Blog

Ransomware

Thought Leadership

RESPOND

The Future of Cyber Security: 2022 Predictions by Darktrace

Default blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog image
06
Jan 2022
06
Jan 2022
Discover cyber security predictions for 2022 by Darktrace's experts. Learn how to navigate future cyber threats and enhance your security strategy!

2021年には、Kaseyaサプライチェーンランサムウェア攻撃から、フロリダの水道に有害物質が加えられようとした攻撃、そして既に大きな問題となっているLog4Shell 脆弱性まで、歴史上最も重大なサイバー攻撃のいくつかが発生しています。

DarktraceのサイバーおよびAIエキスパートは昨年、防御型サイバーセキュリティ空間に多くの重要なAIイノベーションを提供しただけでなく、このAIを使って巧妙なサイバー攻撃に応戦し、勝つ方法を世界中の6,500を超える組織にアドバイスしてきました。

そこで私達はこれらのエキスパート達に対し、2022年のサイバーセキュリティについて聞いてみました。

"2022年、ソフトウェアサプライチェーン攻撃は当たり前になる"

Justin Fier, Director of Cyber Intelligence & Analytics

当社の調査では、2021年に最も攻撃を受けた産業は情報技術(IT)および通信セクターでした。実は2020年には、金融サービス業界だったのです。SolarWinds、Kaseya、GitLabなどの大きく報道されたソフトウェアサプライチェーン攻撃、そして最近では、広範に使われているソフトウェアライブラリに組み込まれ数十億台のデバイスが脅威にさらされた‘Log4Shell’ 脆弱性などを考えれば、このシフトは明白でしょう。

攻撃者達は、ソフトウェアおよび開発者インフラ、プラットフォーム、そしてプロバイダーを、ますます政府、企業、重要インフラへの侵入ベクトルとして見るようになっています。脅威アクター達は悪意あるソフトウェアを、ソースコード、開発者のレポジトリ、オープンソースライブラリ、その他ソフトウェアサプライチェーン全体に渡って幅広く埋め込むことが予想されます。私達はおそらく、ソフトウェアプラットフォームに対するさらなるサプライチェーン攻撃や、その他の公開された脆弱性に対する攻撃を目撃することになるでしょう。

また、2021年11月に発生したFBIのアカウント乗っ取りで見られたように、攻撃者はEメール攻撃を進化させ、より直接的に通信のやりとりを乗っ取り、本物の信頼のおけるアカウントからスピアフィッシングEメールを送るようになるでしょう。

攻撃者が開発プロセスの最初の段階から自身を組み込むことができるならば、組織は攻撃者が侵入してしまった後でこれらを検知し阻止できなければなりません。これらの脅威に対し、セキュリティを開発プロセスのより早い段階で組み込む必要性、および攻撃をすばやく封じ込めてビジネスの中断を防ぐことの重要性が再確認されています。これらの攻撃は多段階で行われるものであり、そのあらゆる段階でAIを使って脅威を封じ込め修正することができます。

もっと読む

"'2022年のランサムウェア:より多数の、姿を変えたランサムウェアが出現"

Marcus Fowler, Director of Strategic Threat

世界的なパンデミックと並行して、、ランサムウェアのパンデミックも拡大しています。Darktraceの研究者は、米国内の組織に対する攻撃が2021年には2020年の3倍に増え、英国内では2倍に増えたことを確認しています。

この危機に際し、30か国が協力してランサムウェアに対する取り組みについて議論し、暗号通貨規制、セキュリティレジリエンス、攻撃の阻止、国際的なサイバー外交などについて検討することになりました。こうした画期的な政策にも関わらず、また政府の圧力によりランサムウェアグループを解散させ、あるいはランサムウェアギャングの刑事責任を追及しても、これらのグループは名前を変え、さらに高度なテクニックや能力を身につけて再び出現するでしょう。

ランサムウェアの侵入を許した場合、攻撃者は2022年にはテクニックを進化させ、クラウドサービスプロバイダやバックアップおよびアーカイブプロバイダを標的にする可能性もあります。そしてこれらの問題を単にIT上の不便として見ることができない、組織が耐えることのできない問題となる時が来ます。重要インフラを担う組織や企業は一様に、攻撃発生後どれだけ迅速にオペレーションを復旧できるか、そして身代金の支払いや高価なシステム修復などにおいて、サイバー保険会社にどれだけの期間頼ることができるか、およびそのための費用について検討を続けることになるでしょう。

ランサムウェアに対する防御が持続可能でなくなった場合、何が答えとなるでしょうか?最終的には、組織はサイバー攻撃に耐えることのできるシステムを構築するでしょう。それまでの間、組織に必要なのは学習し、細かな意思決定を行い、状況に見合った対処を行うことにより、データ抜き出しや暗号化が発生する前の十分に早い段階で攻撃を検知し阻止するセキュリティソフトウェアです。

もっと読む

"人間とAIの関係は、説明能力により強化されるだろう"

Max Heinemeyer, Director of Threat Hunting

防御担当者達は組織の存亡を左右するサイバー攻撃の脅威に対し、脅威の検知から自律的マイクロデシジョンの使用、そしてマシンスピードでの攻撃への対処まで、これまで10年近くに渡ってAIを適用してきました。セキュリティチームが最高の状態で機能するためのブレイクスルーは、こうした高度な数学アルゴリズムだけによるものではないかもしれません。2022年には、説明可能なAI(XAI:Explainable Artificial Intelligence)によりそれらが実現されるでしょう。

機械学習が作成した結果と出力を人間が理解し信頼できるようにするためのプロセス及び手法は、セキュリティオペレーションセンター(SOC)の中心となるでしょう。単なる警告までの時間ではなく、理解するまでの時間を重視することで、セキュリティチームの有効性を計る方法が進化します。セキュリティエキスパート達はAIの予想する影響とその潜在的なバイアスについて理解したいと考えているため、「ブラックボックス」的概念と際立って対照的なXAIへの注目が高まるでしょう。

この例としては、自然言語処理(NLP:Natural Language Processing)を使ってサイバー攻撃についての仮説、AIが実行したステップ、それらのステップの結果、推奨されるアクション、ひいては攻撃が再度発生しないようにするための方法までを説明することが含まれます。

"「大量退職時代」は内部関係者脅威の増加につながる"

Toby Lewis, Head of Threat Analysis

パンデミックによる従業員「大量退職時代」においては、不満を持った従業員が情報を盗む、あるいは従業員が意図せず次の仕事に情報を持って行ってしまう、ということが起こり得ます。また、犯罪者グループが多額の金銭あるいは身代金の一部を提示して内部関係者を勧誘する、という例もありました。

意図の有無にかかわらず、2022年には内部関係者対策が企業にとってますます大きな問題となるでしょう。クラウドを使ったコミュニケーションやコラボレーションアプリケーションを使う組織が増える中、肥大化したデジタルインフラ内でこれらの脅威を検知することはより困難となります。従業員がリモートで働くようになると、機器やデータの返却を徹底することもさらに難しくなります。

そして、組織は従業員の行動を複数の角度、たとえばクラウド、SaaS、エンドポイントなどから理解するためのセキュリティテクノロジーにより大きく依存するようになるでしょう。このテクノロジーは、従業員がEメールを外部に送信する、通常はアクセスしないファイルにアクセスする、その他異常な操作をするなど、その人らしくない振る舞いをしたときに自動的にアクションを取るものです。これらのアプローチは新たなゼロトラストテクノロジーと共に機能し、ゼロトラストアーキテクチャに従って組織を内部関係者による脅威から守ります。

"AIイノベーションは防御者がプロアクティブに攻撃をシミュレートするのに役立つ"

Nicole Eagan, Chief Strategy Officer, AI Officer

AIは防御型サイバーセキュリティ空間において、脅威検知、調査、対処などに対するさまざまな重要イノベーションを提供してきました。2022年にはAIイノベーションは防御中心から、プロアクティブなセキュリティおよび攻撃シミュレーションなどの周囲分野に拡大するでしょう。

最新の進化により、AIを使って攻撃経路モデリング、敵対シミュレーション、継続的レッドチーミングなどを実行することが可能になり、組織は最も蓋然性の高い問題シナリオを可視化しテストすることにより、安全策やコントロールを適用してサイバーリスクを低減することができるようになります。サイバーセキュリティ組織にとっての基本的重要項目も、脆弱性を見つけ出し、コントロールされた攻撃を実行して防御をテストする新しいテクノロジーにより力を入れていくにつれ、形を変えていくでしょう。

サイバーリスク管理に対するこれらのいわゆる積極型、予測型のアプローチは、まだ経営層に浸透しているとは言えませんが、企業、規制当局、監査コミュニティ、サイバー保険会社が将来のサイバーリスクを評価するやり方を変えていく可能性があります。

これらの予測の基礎となる考察を提供してくれたDarktrace社内の各分野のエキスパート諸氏に感謝します。

INSIDE THE SOC
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
AUTHOR
ABOUT ThE AUTHOR
Justin Fier
SVP, Red Team Operations

Justin is one of the US’s leading cyber intelligence experts, and holds the position of SVP, Red Team Operations at Darktrace. His insights on cyber security and artificial intelligence have been widely reported in leading media outlets, including the Wall Street Journal, CNN, The Washington Post, and VICELAND. With over 10 years’ experience in cyber defense, Justin has supported various elements in the US intelligence community, holding mission-critical security roles with Lockheed Martin, Northrop Grumman Mission Systems and Abraxas. Justin is also a highly-skilled technical specialist, and works with Darktrace’s strategic global customers on threat analysis, defensive cyber operations, protecting IoT, and machine learning.

Book a 1-1 meeting with one of our experts
この記事を共有
COre coverage

More in this series

該当する項目はありません。

Blog

該当する項目はありません。

The State of AI in Cybersecurity: How AI will impact the cyber threat landscape in 2024

Default blog imageDefault blog image
22
Apr 2024

About the AI Cybersecurity Report

We surveyed 1,800 CISOs, security leaders, administrators, and practitioners from industries around the globe. Our research was conducted to understand how the adoption of new AI-powered offensive and defensive cybersecurity technologies are being managed by organizations.

This blog is continuing the conversation from our last blog post “The State of AI in Cybersecurity: Unveiling Global Insights from 1,800 Security Practitioners” which was an overview of the entire report. This blog will focus on one aspect of the overarching report, the impact of AI on the cyber threat landscape.

To access the full report click here.

Are organizations feeling the impact of AI-powered cyber threats?

Nearly three-quarters (74%) state AI-powered threats are now a significant issue. Almost nine in ten (89%) agree that AI-powered threats will remain a major challenge into the foreseeable future, not just for the next one to two years.

However, only a slight majority (56%) thought AI-powered threats were a separate issue from traditional/non AI-powered threats. This could be the case because there are few, if any, reliable methods to determine whether an attack is AI-powered.

Identifying exactly when and where AI is being applied may not ever be possible. However, it is possible for AI to affect every stage of the attack lifecycle. As such, defenders will likely need to focus on preparing for a world where threats are unique and are coming faster than ever before.

a hypothetical cyber attack augmented by AI at every stage

Are security stakeholders concerned about AI’s impact on cyber threats and risks?

The results from our survey showed that security practitioners are concerned that AI will impact organizations in a variety of ways. There was equal concern associated across the board – from volume and sophistication of malware to internal risks like leakage of proprietary information from employees using generative AI tools.

What this tells us is that defenders need to prepare for a greater volume of sophisticated attacks and balance this with a focus on cyber hygiene to manage internal risks.

One example of a growing internal risks is shadow AI. It takes little effort for employees to adopt publicly-available text-based generative AI systems to increase their productivity. This opens the door to “shadow AI”, which is the use of popular AI tools without organizational approval or oversight. Resulting security risks such as inadvertent exposure of sensitive information or intellectual property are an ever-growing concern.

Are organizations taking strides to reduce risks associated with adoption of AI in their application and computing environment?

71.2% of survey participants say their organization has taken steps specifically to reduce the risk of using AI within its application and computing environment.

16.3% of survey participants claim their organization has not taken these steps.

These findings are good news. Even as enterprises compete to get as much value from AI as they can, as quickly as possible, they’re tempering their eager embrace of new tools with sensible caution.

Still, responses varied across roles. Security analysts, operators, administrators, and incident responders are less likely to have said their organizations had taken AI risk mitigation steps than respondents in other roles. In fact, 79% of executives said steps had been taken, and only 54% of respondents in hands-on roles agreed. It seems that leaders believe their organizations are taking the needed steps, but practitioners are seeing a gap.

Do security professionals feel confident in their preparedness for the next generation of threats?

A majority of respondents (six out of every ten) believe their organizations are inadequately prepared to face the next generation of AI-powered threats.

The survey findings reveal contrasting perceptions of organizational preparedness for cybersecurity threats across different regions and job roles. Security administrators, due to their hands-on experience, express the highest level of skepticism, with 72% feeling their organizations are inadequately prepared. Notably, respondents in mid-sized organizations feel the least prepared, while those in the largest companies feel the most prepared.

Regionally, participants in Asia-Pacific are most likely to believe their organizations are unprepared, while those in Latin America feel the most prepared. This aligns with the observation that Asia-Pacific has been the most impacted region by cybersecurity threats in recent years, according to the IBM X-Force Threat Intelligence Index.

The optimism among Latin American respondents could be attributed to lower threat volumes experienced in the region, but it's cautioned that this could change suddenly (1).

What are biggest barriers to defending against AI-powered threats?

The top-ranked inhibitors center on knowledge and personnel. However, issues are alluded to almost equally across the board including concerns around budget, tool integration, lack of attention to AI-powered threats, and poor cyber hygiene.

The cybersecurity industry is facing a significant shortage of skilled professionals, with a global deficit of approximately 4 million experts (2). As organizations struggle to manage their security tools and alerts, the challenge intensifies with the increasing adoption of AI by attackers. This shift has altered the demands on security teams, requiring practitioners to possess broad and deep knowledge across rapidly evolving solution stacks.

Educating end users about AI-driven defenses becomes paramount as organizations grapple with the shortage of professionals proficient in managing AI-powered security tools. Operationalizing machine learning models for effectiveness and accuracy emerges as a crucial skill set in high demand. However, our survey highlights a concerning lack of understanding among cybersecurity professionals regarding AI-driven threats and the use of AI-driven countermeasures indicating a gap in keeping pace with evolving attacker tactics.

The integration of security solutions remains a notable problem, hindering effective defense strategies. While budget constraints are not a primary inhibitor, organizations must prioritize addressing these challenges to bolster their cybersecurity posture. It's imperative for stakeholders to recognize the importance of investing in skilled professionals and integrated security solutions to mitigate emerging threats effectively.

To access the full report click here.

参考文献

1. IBM, X-Force Threat Intelligence Index 2024, Available at: https://www.ibm.com/downloads/cas/L0GKXDWJ

2. ISC2, Cybersecurity Workforce Study 2023, Available at: https://media.isc2.org/-/media/Project/ISC2/Main/Media/ documents/research/ISC2_Cybersecurity_Workforce_Study_2023.pdf?rev=28b46de71ce24e6ab7705f6e3da8637e

続きを読む
著者について

Blog

Inside the SOC

Sliver C2: How Darktrace Provided a Sliver of Hope in the Face of an Emerging C2 Framework

Default blog imageDefault blog image
17
Apr 2024

Offensive Security Tools

As organizations globally seek to for ways to bolster their digital defenses and safeguard their networks against ever-changing cyber threats, security teams are increasingly adopting offensive security tools to simulate cyber-attacks and assess the security posture of their networks. These legitimate tools, however, can sometimes be exploited by real threat actors and used as genuine actor vectors.

What is Sliver C2?

Sliver C2 is a legitimate open-source command-and-control (C2) framework that was released in 2020 by the security organization Bishop Fox. Silver C2 was originally intended for security teams and penetration testers to perform security tests on their digital environments [1] [2] [5]. In recent years, however, the Sliver C2 framework has become a popular alternative to Cobalt Strike and Metasploit for many attackers and Advanced Persistence Threat (APT) groups who adopt this C2 framework for unsolicited and ill-intentioned activities.

The use of Sliver C2 has been observed in conjunction with various strains of Rust-based malware, such as KrustyLoader, to provide backdoors enabling lines of communication between attackers and their malicious C2 severs [6]. It is unsurprising, then, that it has also been leveraged to exploit zero-day vulnerabilities, including critical vulnerabilities in the Ivanti Connect Secure and Policy Secure services.

In early 2024, Darktrace observed the malicious use of Sliver C2 during an investigation into post-exploitation activity on customer networks affected by the Ivanti vulnerabilities. Fortunately for affected customers, Darktrace DETECT™ was able to recognize the suspicious network-based connectivity that emerged alongside Sliver C2 usage and promptly brought it to the attention of customer security teams for remediation.

How does Silver C2 work?

Given its open-source nature, the Sliver C2 framework is extremely easy to access and download and is designed to support multiple operating systems (OS), including MacOS, Windows, and Linux [4].

Sliver C2 generates implants (aptly referred to as ‘slivers’) that operate on a client-server architecture [1]. An implant contains malicious code used to remotely control a targeted device [5]. Once a ‘sliver’ is deployed on a compromised device, a line of communication is established between the target device and the central C2 server. These connections can then be managed over Mutual TLS (mTLS), WireGuard, HTTP(S), or DNS [1] [4]. Sliver C2 has a wide-range of features, which include dynamic code generation, compile-time obfuscation, multiplayer-mode, staged and stageless payloads, procedurally generated C2 over HTTP(S) and DNS canary blue team detection [4].

Why Do Attackers Use Sliver C2?

Amidst the multitude of reasons why malicious actors opt for Sliver C2 over its counterparts, one stands out: its relative obscurity. This lack of widespread recognition means that security teams may overlook the threat, failing to actively search for it within their networks [3] [5].

Although the presence of Sliver C2 activity could be representative of authorized and expected penetration testing behavior, it could also be indicative of a threat actor attempting to communicate with its malicious infrastructure, so it is crucial for organizations and their security teams to identify such activity at the earliest possible stage.

Darktrace’s Coverage of Sliver C2 Activity

Darktrace’s anomaly-based approach to threat detection means that it does not explicitly attempt to attribute or distinguish between specific C2 infrastructures. Despite this, Darktrace was able to connect Sliver C2 usage to phases of an ongoing attack chain related to the exploitation of zero-day vulnerabilities in Ivanti Connect Secure VPN appliances in January 2024.

Around the time that the zero-day Ivanti vulnerabilities were disclosed, Darktrace detected an internal server on one customer network deviating from its expected pattern of activity. The device was observed making regular connections to endpoints associated with Pulse Secure Cloud Licensing, indicating it was an Ivanti server. It was observed connecting to a string of anomalous hostnames, including ‘cmjk3d071amc01fu9e10ae5rt9jaatj6b.oast[.]live’ and ‘cmjft14b13vpn5vf9i90xdu6akt5k3pnx.oast[.]pro’, via HTTP using the user agent ‘curl/7.19.7 (i686-redhat-linux-gnu) libcurl/7.63.0 OpenSSL/1.0.2n zlib/1.2.7’.

Darktrace further identified that the URI requested during these connections was ‘/’ and the top-level domains (TLDs) of the endpoints in question were known Out-of-band Application Security Testing (OAST) server provider domains, namely ‘oast[.]live’ and ‘oast[.]pro’. OAST is a testing method that is used to verify the security posture of an application by testing it for vulnerabilities from outside of the network [7]. This activity triggered the DETECT model ‘Compromise / Possible Tunnelling to Bin Services’, which breaches when a device is observed sending DNS requests for, or connecting to, ‘request bin’ services. Malicious actors often abuse such services to tunnel data via DNS or HTTP requests. In this specific incident, only two connections were observed, and the total volume of data transferred was relatively low (2,302 bytes transferred externally). It is likely that the connections to OAST servers represented malicious actors testing whether target devices were vulnerable to the Ivanti exploits.

The device proceeded to make several SSL connections to the IP address 103.13.28[.]40, using the destination port 53, which is typically reserved for DNS requests. Darktrace recognized that this activity was unusual as the offending device had never previously been observed using port 53 for SSL connections.

Model Breach Event Log displaying the ‘Application Protocol on Uncommon Port’ DETECT model breaching in response to the unusual use of port 53.
Figure 1: Model Breach Event Log displaying the ‘Application Protocol on Uncommon Port’ DETECT model breaching in response to the unusual use of port 53.

Figure 2: Model Breach Event Log displaying details pertaining to the ‘Application Protocol on Uncommon Port’ DETECT model breach, including the 100% rarity of the port usage.
Figure 2: Model Breach Event Log displaying details pertaining to the ‘Application Protocol on Uncommon Port’ DETECT model breach, including the 100% rarity of the port usage.

Further investigation into the suspicious IP address revealed that it had been flagged as malicious by multiple open-source intelligence (OSINT) vendors [8]. In addition, OSINT sources also identified that the JARM fingerprint of the service running on this IP and port (00000000000000000043d43d00043de2a97eabb398317329f027c66e4c1b01) was linked to the Sliver C2 framework and the mTLS protocol it is known to use [4] [5].

An Additional Example of Darktrace’s Detection of Sliver C2

However, it was not just during the January 2024 exploitation of Ivanti services that Darktrace observed cases of Sliver C2 usages across its customer base.  In March 2023, for example, Darktrace detected devices on multiple customer accounts making beaconing connections to malicious endpoints linked to Sliver C2 infrastructure, including 18.234.7[.]23 [10] [11] [12] [13].

Darktrace identified that the observed connections to this endpoint contained the unusual URI ‘/NIS-[REDACTED]’ which contained 125 characters, including numbers, lower and upper case letters, and special characters like “_”, “/”, and “-“, as well as various other URIs which suggested attempted data exfiltration:

‘/upload/api.html?c=[REDACTED] &fp=[REDACTED]’

  • ‘/samples.html?mx=[REDACTED] &s=[REDACTED]’
  • ‘/actions/samples.html?l=[REDACTED] &tc=[REDACTED]’
  • ‘/api.html?gf=[REDACTED] &x=[REDACTED]’
  • ‘/samples.html?c=[REDACTED] &zo=[REDACTED]’

This anomalous external connectivity was carried out through multiple destination ports, including the key ports 443 and 8888.

Darktrace additionally observed devices on affected customer networks performing TLS beaconing to the IP address 44.202.135[.]229 with the JA3 hash 19e29534fd49dd27d09234e639c4057e. According to OSINT sources, this JA3 hash is associated with the Golang TLS cipher suites in which the Sliver framework is developed [14].

結論

Despite its relative novelty in the threat landscape and its lesser-known status compared to other C2 frameworks, Darktrace has demonstrated its ability effectively detect malicious use of Sliver C2 across numerous customer environments. This included instances where attackers exploited vulnerabilities in the Ivanti Connect Secure and Policy Secure services.

While human security teams may lack awareness of this framework, and traditional rules and signatured-based security tools might not be fully equipped and updated to detect Sliver C2 activity, Darktrace’s Self Learning AI understands its customer networks, users, and devices. As such, Darktrace is adept at identifying subtle deviations in device behavior that could indicate network compromise, including connections to new or unusual external locations, regardless of whether attackers use established or novel C2 frameworks, providing organizations with a sliver of hope in an ever-evolving threat landscape.

Credit to Natalia Sánchez Rocafort, Cyber Security Analyst, Paul Jennings, Principal Analyst Consultant

付録

DETECT Model Coverage

  • Compromise / Repeating Connections Over 4 Days
  • Anomalous Connection / Application Protocol on Uncommon Port
  • Anomalous Server Activity / Server Activity on New Non-Standard Port
  • Compromise / Sustained TCP Beaconing Activity To Rare Endpoint
  • Compromise / Quick and Regular Windows HTTP Beaconing
  • Compromise / High Volume of Connections with Beacon Score
  • Anomalous Connection / Multiple Failed Connections to Rare Endpoint
  • Compromise / Slow Beaconing Activity To External Rare
  • Compromise / HTTP Beaconing to Rare Destination
  • Compromise / Sustained SSL or HTTP Increase
  • Compromise / Large Number of Suspicious Failed Connections
  • Compromise / SSL or HTTP Beacon
  • Compromise / Possible Malware HTTP Comms
  • Compromise / Possible Tunnelling to Bin Services
  • Anomalous Connection / Low and Slow Exfiltration to IP
  • Device / New User Agent
  • Anomalous Connection / New User Agent to IP Without Hostname
  • Anomalous File / EXE from Rare External Location
  • Anomalous File / Numeric File Download
  • Anomalous Connection / Powershell to Rare External
  • Anomalous Server Activity / New Internet Facing System

侵害指標(IoC)一覧

18.234.7[.]23 - Destination IP - Likely C2 Server

103.13.28[.]40 - Destination IP - Likely C2 Server

44.202.135[.]229 - Destination IP - Likely C2 Server

参考文献

[1] https://bishopfox.com/tools/sliver

[2] https://vk9-sec.com/how-to-set-up-use-c2-sliver/

[3] https://www.scmagazine.com/brief/sliver-c2-framework-gaining-traction-among-threat-actors

[4] https://github[.]com/BishopFox/sliver

[5] https://www.cybereason.com/blog/sliver-c2-leveraged-by-many-threat-actors

[6] https://securityaffairs.com/158393/malware/ivanti-connect-secure-vpn-deliver-krustyloader.html

[7] https://www.xenonstack.com/insights/out-of-band-application-security-testing

[8] https://www.virustotal.com/gui/ip-address/103.13.28.40/detection

[9] https://threatfox.abuse.ch/browse.php?search=ioc%3A107.174.78.227

[10] https://threatfox.abuse.ch/ioc/1074576/

[11] https://threatfox.abuse.ch/ioc/1093887/

[12] https://threatfox.abuse.ch/ioc/846889/

[13] https://threatfox.abuse.ch/ioc/1093889/

[14] https://github.com/projectdiscovery/nuclei/issues/3330

続きを読む
著者について
Natalia Sánchez Rocafort
Cyber Security Analyst
Our ai. Your data.

Elevate your cyber defenses with Darktrace AI

無償トライアルを開始
Darktrace AI protecting a business from cyber threats.