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August 2, 2023

Darktrace's Detection of Ransomware & Syssphinx

Read how Darktrace identified an attack technique by the threat group, Syssphinx. Learn how Darktrace's quick identification process can spot a threat.
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.
Written by
Adam Potter
Senior Cyber Analyst
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02
Aug 2023

Introduction

As the threat of costly cyber-attacks continues represent a real concern to security teams across the threat landscape, more and more organizations are strengthening their defenses with additional security tools to identify attacks and protect their networks. As a result, malicious actors are being forced to adapt their tactics, modify existing variants of malicious software, or utilize entirely new variants.  

Symantec recently released an article about Syssphinx, the financially motivated cyber threat group previously known for their point-of-sale attacks. Syssphinx attempts to deploy ransomware on customer networks via a modified version of their ‘Sardonic’ backdoor. Such activity highlights the ability of threat actors to alter the composition and presentation of payloads, tools, and tactics.

Darktrace recently detected some of the same indicators suggesting a likely Syssphinx compromise within the network of a customer trialing the Darktrace DETECT™ and RESPOND™ products. Despite the potential for variations in the construction of backdoors and payloads used by the group, Darktrace’s anomaly-based approach to threat detection allowed it to stitch together a detailed account of compromise activity and identify the malicious activity prior to disruptive events on the customer’s network.

What is Syssphinx?

Syssphinx is a notorious cyber threat entity known for its financially motivated compromises.  Also referred to as FIN8, Syssphinx has been observed as early as 2016 and is largely known to target private sector entities in the retail, hospitality, insurance, IT, and financial sectors.[1]

Although Syssphinx primarily began focusing on point-of-sale style attacks, the activity associated with the group has more recently incorporated ransomware variants into their intrusions in a potential bid to further extract funds from target organizations.[2]

Syssphinx Sardonic Backdoor

Given this gradual opportunistic incorporation of ransomware, it should not be surprising that Syssphinx has slowly expanded its repertoire of tools.  When primarily performing point-of-sale compromises, the group was known for its use of point-of-sale specific malwares including BadHatch, PoSlurp/PunchTrack, and PowerSniff/PunchBuggy/ShellTea.[3]

However, in a seeming response to updates in detection systems while using previous indicators of compromise (IoCs), Syssphinx began to modify its BadHatch malware.  This resulted in the use of a C++ derived backdoor known as “Sardonic”, which has the ability to aggregate host credentials, spawn additional command sessions, and deliver payloads to compromised devices via dynamic-link library (DLL).[4],[5]

Analysis of the latest version of Sardonic reveals further changes to the malware to elude detection. These shifts include the implementation of the backdoor in the C programming language, and additional over-the-network communication obfuscation techniques. [6]

During the post-exploitation phase, the group tends to rely on “living-off-the-land” tactics, whereby an attacker utilizes tools already present within the organization’s digital environment to avoid detection. Syssphinx seems to utilize system-native tools such as PowerShell and the Windows Management Instrumentation (WMI) interface.[7] It is also not uncommon to see Windows-based vulnerability exploits employed on compromised devices. This has been observed by researchers who have examined previous iterations of Syssphinx backdoors.[8] Syssphinx also appears to exhibit elements of strategic patience and discipline in its operations, with significant time gaps in operations noted by researchers. During this time, it appears likely that updates and tweaks were applied to Syssphinx payloads.

Compromise Details

In late April 2023, Darktrace identified an active compromise on the network of a prospective customer who was trialing Darktrace DETECT+RESPOND. The customer, a retailer in EMEA with hundreds of tracked devices, reached out to the Darktrace Analyst team via the Ask the Expert (ATE) service for support and further investigation, following the encryption of their server and backup data storage in an apparent ransomware attack. Although the encryption events fell outside Darktrace’s purview due to a limited set up of trial appliances, Darktrace was able to directly track early stages of the compromise before exfiltration and encryption events began. If a full deployment had been set up and RESPOND functionality had been configured in autonomous response mode, Darktrace may have helped mitigate such encryption events and would have aided in the early identification of this ransomware attack.

Initial Intrusion and Establishment of Command and Control (C2) Infrastructure

As noted by security researchers, Syssphinx largely relies on social engineering and phishing emails to deliver its backdoor payloads. As there were no Darktrace/Email™ products deployed for this customer, it would be difficult to directly observe the exact time and manner of initial payload delivery related to this compromise. This is compounded by the fact that the customer had only recently began using Darktrace’s products during their trial period. Given the penchant for patience and delay by Syssphinx, it is possible that the intrusion began well before Darktrace had visibility of the organization’s network.

However, beginning on April 30, 2023, at 07:17:31 UTC, Darktrace observed the domain controller dc01.corp.XXXX  making repeated SSL connections to the endpoint 173-44-141-47[.]nip[.]io. In addition to the multiple open-source intelligence (OSINT) flags for this endpoint, the construction of the domain parallels that of the initial domain used to deliver a backdoor, as noted by Symantec in their analysis (37-10-71-215[.]nip[.]io). This activity likely represented the initial beaconing being performed by the compromised device. Additionally, an elevated level of incoming external data over port 443 was observed during this time, which may be associated with the delivery of the Sardonic backdoor payload. Given the unusual use of port 443 to perform SSH connections later seen in the kill chain of this attack, this activity could also parallel the employment of embedded backdoor payloads seen in the latest iteration of the Sardonic backdoor noted by Symantec.

Figure 1: Graph of the incoming external data surrounding the time of the initial establishment of command and control communication for the domain controller. As seen in the graph, the spike in incoming external data during this time may parallel the delivery of Syssphinx Sardonic backdoor.

Regardless, the domain controller proceeded to make repeated connections over port 443 to the noted domain.

Figure 2: Breach event log for the domain controller making repeated connections over port 443 to the rare external destination endpoint in constitute the establishment of C2 communication.

Internal Reconnaissance/Privilege Escalation

Following the establishment of C2 communication, Darktrace detected numerous elements of internal reconnaissance. On Apr 30, 2023, at 22:06:26 UTC, the desktop device desktop_02.corp.XXXX proceeded to perform more than 100 DRSGetNCChanges requests to the aforementioned domain controller. These commands, which are typically implemented over the RPC protocol on the DRSUAPI interface, are frequently utilized in Active Directory sync attacks to copy Active Directory information from domain controllers. Such activity, when not performed by new domain controllers to sync Active Directory contents, can indicate malicious domain or user enumeration, credential compromise or Active Directory enumeration.

Although the affected device made these requests to the previously noted domain controller, which was already compromised, such activity may have further enabled the compromise by allowing the threat actor to transfer these details to a more easily manageable device.

The device performing these DRSGetNCChanges requests would later be seen performing lateral movement activity and making connections to malicious endpoints.

Figure 3: Breach log highlighting the DRS operations performed by the corporate device to the destination domain controller. Such activity is rarely authorized for devices not tagged as administrative or as domain controllers.

Execution and Lateral Movement

At 23:09:53 UTC on April 30, 2023, the original domain server proceeded to make multiple uncommon WMI calls to a destination server on the same subnet (server01.corp.XXXX). Specifically, the device was observed making multiple RPC calls to IWbem endpoints on the server, which included login and ExecMethod (method execution) commands on the destination device. This destination device later proceeded to conduct additional beaconing activity to C2 endpoints and exfiltrate data.

Figure 4: Breach log for the domain controller performing WMI commands to the destination server during the lateral movement phase of the breach.

Similarly, beginning on May 1, 2023, at 00:11:09 UTC, the device desktop_02.corp.XXXX made multiple WMI requests to two additional devices, one server and one desktop, within the same subnet as the original domain controller. During this time, desktop_02.corp.XXXX  also utilized SMBv1, an outdated and typically non-compliant version communication protocol, to write the file rclone.exe to the same two destination devices. Rclone.exe, and its accompanying bat file, is a command-line tool developed by IT provider Rclone, to perform file management tasks. During this time, Darktrace also observed the device reading and deleting an unexpected numeric file on the ADMIN$ of the destination server, which may represent additional defense evasion techniques and tool staging.

Figure 5: Event log highlighting the writing of rclone.exe using the outdated SMBv1 communication protocol.
Figure 6: SMB logs indicating the reading and deletion of numeric string files on ADMIN$ shares of the destination devices during the time of the rclone.exe SMB writes. Such activity may be associated with tool staging and could indicate potential defense evasion techniques.

Given that the net loader sample analyzed by Symantec injects the backdoor into a WmiPrvSE.exe process, the use of WMI operations is not unexpected. Employment of WMI also correlates with the previously mentioned “living-off-the-land” tactics, as WMI services are commonly used for regular network and system administration purposes. Moreover, the staging of rclone.exe, a legitimate file management tool, for data exfiltration underscores attempts to blend into existing and expected network traffic and remain undetected on the customer’s network.

Data Exfiltration and Impact

Initial stages of data exfiltration actually began prior to some of the lateral movement events described above. On April 30, 2023, 23:09:47 the device server01.corp.XXXX, transferred nearly 11 GB of data to 173.44[.]141[.]47, as well as to the rare external IP address 170.130[.]55[.]77, which appears to have served as the main exfiltration destination during this compromise. Furthermore, the host made repeated connections to the same external IP associated with the initial suspicious beaconing activity (173.44[.]141[.]47) over SSL.

While the data exfiltration event unfolded, the device, server01.corp.XXXX, made multiple HTTP requests to 37.10[.]71[.]215, which featured URIs requesting the rclone.exe and rclone.bat files. This IP address was directly involved in the sample analyzed by Symantec. Furthermore, one of the devices that received the SMB file writes of rclone.exe and the WMI commands from desktop_02.corp.XXXX also performed SSL beaconing to endpoints associated with the compromise.

Between 01:20:45 - 03:31:41 UTC on May 1, 2023, a Darktrace detected a series of devices on the network performing a repeated pattern of activity, namely external connectivity followed by suspicious file downloads and external data transfer operations. Specifically, each affected device made multiple HTTP requests to 37.10[.]71[.]215 for rclone files. The devices proceeded to download the executable and/or binary files, and then transfer large amounts of data to the aforementioned endpoints, 170.130[.]55[.]77 and or 173-44-141-47[.]nip[.]io. Although the devices involved in data exfiltration utilized port 443 as a destination port, the connections actually used the SSH protocol. Darktrace recognized this behavior as unusual as port 443 is typically associated with the SSL protocol, while port 22 is reserved for SSH. Therefore, this activity may represent the threat actor’s attempts to remain undetected by security tools.

This unexpected use of SSH over port 443 also correlates with the descriptions of the new Sardonic backdoor according to threat researchers. Further beaconing and exfiltration activity was performed by an additional host one day later whereby the device made suspicious repeated connections to the aforementioned external hosts.

Figure 7: Connection details highlighting the use of port 443 for SSH connections during the exfiltration events.

In total, nine separate devices were involved in this pattern of activity. Five of these devices were labeled as ‘administrative’ devices according to their hostnames. Over the course of the entire exfiltration event, the attackers exfiltrated almost 61 GB of data from the organization’s environment.

Figure 8: Graph showing the levels of external data transfer from a breach device for one day on either side of the breach time. There is a large spike in such activity during the time of the breach that underscores the exfiltration events.

In addition to the individual anomaly detections by DETECT, Darktrace’s Cyber AI Analyst™ launched an autonomous investigation into the unusual behavior carried out by affected devices, connecting and collating multiple security events into one AI Analyst Incident. AI Analyst ensures that Darktrace can recognize and link the individual steps of a wider attack, rather than just identifying isolated incidents. While traditional security tools may mistake individual breaches as standalone activity, Darktrace’s AI allows it to provide unparalleled visibility over emerging attacks and their kill chains. Furthermore, Cyber AI Analyst’s instant autonomous investigations help to save customer security teams invaluable time in triaging incidents in comparison with human teams who would have to commit precious time and resources to conduct similar pattern analysis.

In this specific case, AI Analyst identified 44 separate security events from 18 different devices and was able to tie them together into one incident. The events that made up this AI Analyst Incident included:

  • Possible SSL Command and Control
  • Possible HTTP Command and Control
  • Unusual Repeated Connections
  • Suspicious Directory Replication ServiceActivity
  • Device / New or Uncommon WMI Activity
  • SMB Write of Suspicious File
  • Suspicious File Download
  • Unusual External Data Transfer
  • Unusual External Data Transfer to MultipleRelated Endpoints
Figure 9: Cyber AI Incident log highlighting multiple unusual anomalies and connecting them into one incident.

Had Darktrace RESPOND been enabled in autonomous response mode on the network of this prospective customer, it would have been able to take rapid mitigative action to block the malicious external connections used for C2 communication and subsequent data exfiltration, ideally halting the attack at this stage. As previously discussed, the limited network configuration of this trial customer meant that the encryption events unfortunately took place outside of Darktrace’s scope. When fully configured on a customer environment, Darktrace DETECT can identify such encryption attempts as soon as they occur. Darktrace RESPOND, in turn, would be able to immediately intervene by applying preventative actions like blocking internal connections that may represent file encryption, or limiting potentially compromised devices to a previously established pattern of life, ensuring they cannot carry out any suspicious activity.

Conclusion

Despite the limitations posed by the customer’s trial configuration, Darktrace demonstrated its ability to detect malicious activity associated with Syssphinx and track it across multiple stages of the kill chain.

Darktrace’s ability to identify the early stages of a compromise and various steps of the kill chain, highlights the necessity for machine learning-enabled, anomaly-based detection. In the face of threats such as Syssphinx, that exhibit the propensity to recast backdoor payloads and incorporate on “living-off-the-land” tactics, signatures and rules-based detection may not prove as effective. While Syssphinx and other threat groups will continue to adopt new tools, methods, and techniques, Darktrace’s Self-Learning AI is uniquely positioned to meet the challenge of such threats.

Appendix

DETECT Model Breaches Observed

•      Anomalous Server Activity / Anomalous External Activity from Critical Network Device

•      Anomalous Connection / Anomalous DRSGetNCChanges Operation

•      Device / New or Uncommon WMI Activity

•      Compliance / SMB Drive Write

•      Anomalous Connection / Data Sent to Rare Domain

•      Anomalous Connection / Uncommon 1 GiB Outbound

•      Unusual Activity / Unusual External Data Transfer

•      Unusual Activity / Unusual External Data to New Endpoints

•      Compliance / SSH to Rare External Destination

•      Anomalous Connection / Unusual SMB Version 1 Connectivity

•      Anomalous File / EXE from Rare External Location

•      Anomalous File / Script from Rare External Location

•      Compromise / Suspicious File and C2

•      Device / Initial Breach Chain Compromise

AI Analyst Incidents Observed

•      Possible SSL Command and Control

•      Possible HTTP Command and Control

•      Unusual Repeated Connections

•      Suspicious Directory Replication Service Activity

•      Device / New or Uncommon WMI Activity

•      SMB Write of Suspicious File

•      Suspicious File Download

•      Unusual External Data Transfer

•      Unusual External Data Transfer to Multiple Related Endpoints

IoCs

IoC - Type - Description

37.10[.]71[.]215 – IP – C2 + payload endpoint

173-44-141-47[.]nip[.]io – Hostname – C2 – payload

173.44[.]141[.]47 – IP – C2 + potential payload

170.130[.]55[.]77 – IP – Data exfiltration endpoint

Rclone.exe – Exe File – Common data tool

Rclone.bat – Script file – Common data tool

MITRE ATT&CK Mapping

Command and Control

T1071 - Application Layer Protocol

T1071.001 – Web protocols

T1573 – Encrypted channels

T1573.001 – Symmetric encryption

T1573.002 – Asymmetric encryption

T1571 – Non-standard port

T1105 – Ingress tool transfer

Execution

T1047 – Windows Management Instrumentation

Credential Access

T1003 – OS Credential Dumping

T1003.006 – DCSync

Lateral Movement

T1570 – Lateral Tool Transfer

T1021 - Remote Services

T1021.002 - SMB/Windows Admin Shares

T1021.006 – Windows Remote Management

Exfiltration

T1048 - Exfiltration Over Alternative Protocol

T1048.001 - Exfiltration Over Symmetric Encrypted Non-C2 Protocol

T1048.002 - Exfiltration Over Symmetric Encrypted Non-C2 Protocol

T1041 - Exfiltration Over C2 Channel

References

[1] https://cyberscoop.com/syssphinx-cybercrime-ransomware/

[2] https://symantec-enterprise-blogs.security.com/blogs/threat-intelligence/Syssphinx-FIN8-backdoor

[3] https://www.bleepingcomputer.com/news/security/fin8-deploys-alphv-ransomware-using-sardonic-malware-variant/

[4] https://symantec-enterprise-blogs.security.com/blogs/threat-intelligence/Syssphinx-FIN8-backdoor

[5] https://thehackernews.com/2023/07/fin8-group-using-modified-sardonic.html

[6] https://symantec-enterprise-blogs.security.com/blogs/threat-intelligence/Syssphinx-FIN8-backdoor

[7] https://symantec-enterprise-blogs.security.com/blogs/threat-intelligence/Syssphinx-FIN8-backdoor

[8] https://www.mandiant.com/resources/blog/windows-zero-day-payment-cards

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.
Written by
Adam Potter
Senior Cyber Analyst

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April 17, 2026

中国系サイバー作戦の進化 - それはサイバーリスクおよびレジリエンスにとって何を意味するか

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サイバーセキュリティにおいては、これまではインシデント、侵害、キャンペーン、そして脅威グループを中心にリスクを整理してきました。これらの要素は現在も重要です -しかし個別のインシデントにとらわれていては、エコシステム全体の形成を見逃してしまう危険があります。国家が支援する攻撃者グループは、個別の攻撃を実行したり短期的な目標を達成したりするためだけではなく、サイバー作戦を長期的な戦略上の影響力を構築するために使用するようになっています。  

当社の最新の調査レポート、Crimson Echoにおいてもこうした状況にあわせて視点を変えています。キャンペーンやマルウェアファミリー、あるいはアクターのラベルを個別のイベントとして分類するのではなく、ダークトレースの脅威調査チームは中国系グループのアクティビティを長期的に連続した行動として分析しました。このように視野を拡大することで、これらの攻撃者がさまざまな環境内でどのように存在しているか、すなわち、静かに、辛抱強く、持続的に、そして多くのケースにおいて識別可能な「インシデント」が発生するかなり前から下準備をしている様子が明らかになりました。  

中国系サイバー脅威のこれまでの変化

中国系サイバーアクティビティは過去20年間において4つのフェーズで進化してきたと言えます。初期の、ボリュームを重視したオペレーションは1990年代にから2000年代初めに見られ、それが2010年代にはより構造化された、戦略に沿った活動となり、そして現在の高度な適応性を備えた、アイデンティティを中心とした侵入へと進化しています。  

現在のフェーズの特徴は、大規模、攻撃の自制、そして永続化です。攻撃者はアクセスを確立し、その戦略的価値を評価し、維持します。これはより全体的な変化を反映したものです。つまりサイバー作戦は長期的な経済的および地政学的戦略に組み込まれる傾向が強まっているということです。デジタル環境へのアクセス、特に国家の重要インフラやサプライチェーン、先端テクノロジーにつながるものは、ある種の長期的な戦略的影響力と見られるようになりました。  

複雑な問題に対するダークトレースのビヘイビア分析アプローチ

国家が支援するサイバーアクティビティを分析する際、難しい問題の1つはアトリビューションです。従来のアプローチは多くの場合、特定の脅威グループ、マルウェアファミリー、あるいはインフラに判定を依存していました。しかしこれらは絶えず変化するものであり、さらに中国系オペレーションの場合、しばしば重複が見られます。

Crimson Echo は2022年7月から2025年9月の間の3年間にDarktrace運用環境で観測された異常なアクティビティを回顧的に分析した結果です。ビヘイビア検知、脅威ハンティング、オープンソースインテリジェンス、および構造化されたアトリビューションフレームワーク(Darktrace Cybersecurity Attribution Framework)を用いて、数十件の中~高確度の事例を特定し、繰り返し発生しているオペレーションのパターンを分析しました。  

この長期的視野を持ったビヘイビア中心型アプローチにより、ダークトレースは侵入がどのように展開していくかについての一定のパターンを特定することができ、動作のパターンが重要であることがあらためて確認されました。  

データが示していること

分析からいくつかの明確な傾向が浮かび上がりました:

  • 標的は戦略的に重要なセクターに集中していたのです。データセット全体で、侵入の88%は重要インフラと分類される、輸送、重要製造業、政府、医療、ITサービスを含む組織で発生しています。   
  • 戦略的に重要な西側経済圏が主な焦点です。米国だけで、観測されたケースの22.5%を占めており、ドイツ、イタリア、スペイン、および英国を含めた主要なヨーロッパの経済圏と合わせると侵入の半数以上(55%)がこれらの地域に集中しています。  
  • 侵入の63%近くがインターネットに接続されたシステムのエクスプロイトから始まっており、外部に露出したインフラの持続的リスクがあらためて浮き彫りになりました。  

サイバー作戦の2つのモデル

データセット全体で、中国系のアクティビティは2つの作戦モデルに従っていることが確認されました。  

1つ目は“スマッシュアンドグラブ”(強奪)型と表現することができます。これらはスピードのために最適化された短期型の侵入です。攻撃者はすばやく動き  – しばしば48時間以内にデータを抜き出し  – ステルス性よりも規模を重視します。これらの侵害の期間の中央値は10日ほどです。検知の危険を冒しても短期的利益を得ようとしていることが明らかです。  

2つ目は“ローアンドスロー”(低速)型です。これらのオペレーションはデータセット内ではあまり多くありませんでしたが、潜在的影響はより重大です。ここでは攻撃者は持続性を重視し、アイデンティティシステムや正規の管理ツールを通じて永続的なアクセスを確立し、数か月間、場合によっては数年にわたって検知されないままアクセスを維持しようとします。1つの注目すべきケースでは、脅威アクターは環境に完全に侵入して永続性を確立し、600日以上経ってからようやく再浮上した例もありました。このようなオペレーションの一時停止は侵入の深さと脅威アクターの長期的な戦略的意図の両方を表しています。このことはサイバーアクセスが長期にわたって保有し活用するべき戦略的資産であることを示しており、これは最も戦略的に重要なセクターにおいて最もよく見られたパターンです。  

同じ作戦エコシステムにおいて両方のモデルを並行して利用し、標的の価値、緊急性、意図するアクセスに基づいて適切なモデルを選択することも可能だという点に注意することも重要です。“スマッシュアンドグラブ” モデルが見られたからといって諜報活動が失敗したとのみ解釈すべきではなく、むしろ目標に沿った作戦上の選択かもしれないと見るべきでしょう。“ローアンドスロー” 型は粘り強い活動のために最適化され、“スマッシュアンドグラブ” 型はスピードのために最適化されています。どちらも意図的な作戦上の選択と見られ、必ずしも能力を表していません。  

サイバーリスクを再考する

多くの組織にとって、サイバーリスクはいまだに一連の個別のイベントとして位置づけられています。何かが発生し、検知され、封じ込められ、組織はそれを乗り越えて前に進みます。しかし永続的アクセスは、特にクラウド、アイデンティティベースのSaaSやエージェント型システム、そして複雑なサプライチェーンネットワークが相互接続された環境では、重大な持続的露出リスクを作り出します。システムの中断やデータの流出が発生していなくても、そのアクセスによって業務や依存関係、そして戦略的意思決定についての情報を得られるかもしれません。サイバーリスクはますます長期的な競合情報収集に似てきています。

その影響はSOCだけの問題ではありません。組織はガバナンス、可視性、レジリエンスについての考え方を見直し、サイバー露出をインシデント対応の問題ではなく構造的なビジネスリスクとして扱う必要があります。  

次の目標

この調査の目的は、これらの脅威の仕組みについてより明確な理解を提供することにより、防御者がより早期にこれらを識別しより効果的に対応できるようにすることです。これには、インジケーターの追跡からビヘイビアの理解にシフトすること、アイデンティティプロバイダーを重要インフラリスクとして扱うこと、サプライヤーの監視を拡大すること、迅速な封じ込めのための能力に投資すること、などが含まれます。  

ダークトレースの最新調査、”Crimson Echo: ビヘイビア分析を通じて中国系サイバー諜報技術を理解する” についてより詳しく知るには、ビジネスリーダー、CISO、SOCアナリストに向けたCrimson Echoレポートのエグゼクティブサマリーを ここからダウンロードしてください。 

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Nathaniel Jones
VP, Security & AI Strategy, Field CISO

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April 17, 2026

Why Behavioral AI Is the Answer to Mythos

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How AI is breaking the patch-and-prevent security model

The business world was upended last week by the news that Anthropic has developed a powerful new AI model, Claude Mythos, which poses unprecedented risk because of its ability to expose flaws in IT systems.  

Whether it’s Mythos or OpenAI’s GPT-5.4-Cyber, which was just announced on Tuesday, supercharged AI models in the hands of hackers will allow them to carry out attacks at machine speed, much faster than most businesses can stop them.  

This news underscores a stark reality for all leaders: Patching holes alone is not a sufficient control against modern cyberattacks. You must assume that your software is already vulnerable right now. And while LLMs are very good at spotting vulnerabilities, they’re pretty bad at reliably patching them.

Project Glasswing members say it could take months or years for patches to be applied. While that work is done, enterprises must be protected against Zero-Day attacks, or security holes that are still undiscovered.  

Most cybersecurity strategies today are built like a daily multivitamin: broad, preventative, and designed to keep the system generally healthy over time. Patch regularly. Update software. Reduce known vulnerabilities. It’s necessary, disciplined, and foundational. But it’s also built for a world where the risks are well known and defined, cycles are predictable, and exposure unfolds at a manageable pace.

What happens when that model no longer holds?

The AI cyber advantage: Behavioral AI

The vulnerabilities exposed by AI systems like Mythos aren’t the well-understood risks your “multivitamin” was designed to address. They are transient, fast-emerging entry points that exist just long enough to be exploited.

In that environment, prevention alone isn’t enough. You don’t need more vitamins—you need a painkiller. The future of cybersecurity won’t be defined by how well you maintain baseline health. It will be defined by how quickly you respond when something breaks and every second counts.

That’s why behavioral AI gives businesses a durable cyber advantage. Rather than trying to figure out what the attacker looks like, it learns what “normal” looks like across the digital ecosystem of each individual business.  

That’s exactly how behavioral AI works. It understands the self, or what's normal for the organization, and then it can spot deviations in from normal that are actually early-stage attacks.

The Darktrace approach to cybersecurity

At Darktrace, we’ve been defending our 10,000 customers using behavioral AI cybersecurity developed in our AI Research Centre in Cambridge, U.K.

Darktrace was built on the understanding that attacks do not arrive neatly labeled, and that the most damaging threats often emerge before signatures, indicators, or public disclosures can catch up.  

Our AI algorithms learn in real time from your personalized business data to learn what’s normal for every person and every asset, and the flows of data within your organization. By continuously understanding “normal” across your entire digital ecosystem, Darktrace identifies and contains threats emerging from unknown vulnerabilities and compromised supply chain dependencies, autonomously curtailing attacks at machine speed.  

Security for novel threats

Darktrace is built for a world where AI is not just accelerating attacks, but fundamentally reshaping how they originate. What makes our AI so unique is that it's proven time and again to identify cyber threats before public vulnerability disclosures, such as critical Ivanti vulnerabilities in 2025 and SAP NetWeaver exploitations tied to nation-state threat actors.  

As AI reshapes how vulnerabilities are found and exploited, cybersecurity must be anchored in something more durable than a list of known flaws. It requires a real-time understanding of the business itself: what belongs, what does not, and what must be stopped immediately.

What leaders should do right now

The leadership priority must shift accordingly.

First, stop treating unknown vulnerabilities as an edge case. AI‑driven discovery makes them the norm. Security programs built primarily around known flaws, signatures, and threat intelligence will always lag behind an attacker that is operating in real time.

Second, insist on an understanding of what is actually normal across the business. When threats are novel, labels are useless. The earliest and most reliable signal of danger is abnormal behavior—systems, users, or data flows that suddenly depart from what is expected. If you cannot see that deviation as it happens, you are effectively blind during the most critical window.

Finally, assume that the next serious incident will occur before remediation guidance is available. Ask what happens in those first minutes and hours. The organizations that maintain resilience are not the ones waiting for disclosure cycles to catch up—they are the ones that can autonomously identify and contain emerging threats as they unfold.

This is the reality of cybersecurity in an AI‑shaped world. Patching and prevention remain important foundations, but the advantage now belongs to those who can respond instantly when the unpredictable occurs.

Behavioral AI is security designed not just for known threats, but for the ones that AI will discover next.

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Ed Jennings
President and CEO
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