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
Brianna Luong (Leddy)
Sr. Technical Alliances Manager
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27
Sep 2022
Attackers have leveraged social engineering in several high-profile hacks in recent months, with organizations like Uber, Rockstar Games, Cloudflare, Cisco, and LastPass among the most well-known targets.
Social engineering is the manipulation of a user, often through fear or doubt, to coax them into actions like revealing credentials or other sensitive information. The threat landscape is teeming with social engineering attempts across all forms of digital messaging, including email, Slack, and SMS. Moreover, spear-phishing, watering hole attacks, and spoofing are growing increasingly sophisticated.
Organizations are taking numerous defensive measures in response. This includes ramping up security education efforts, as well as configuring multi-factor authentication (MFA). But while MFA strengthens security, it can still be thwarted by hackers, and security awareness training programs often yield mixed or disappointing results. Now, organizations are increasingly turning to artificial intelligence to stop cyber-attacks carried out through social engineering.
Since application-based transportation companies face distinct risks with their complex digital infrastructure, they require dynamic security solutions that adapt to evolving phishing techniques to guarantee reliable service to their customers. To that end, the Bluebird Group, the largest taxi service in Indonesia, has been using Darktrace to protect its email and cloud-based messaging since 2021.
“While we’ve pivoted and shown flexibility in the face of change, so too have the attackers,” said Sigit Djokosoetono, CEO at PT Blue Bird Tbk, a subsidiary of The Bluebird Group. “We’ve seen an uptick in attacks targeting cloud and SaaS applications, for example. Phishing emails are becoming more realistic and more frequent.”
Traditional email defenses lag behind contemporary social engineering threats because they rely on threat intelligence and collecting “deny-lists” of email domains and IP addresses already recognized as bad. But attackers can set up new domains for pennies and update infrastructure too frequently for this method to have effect.
Darktrace’s unique approach to cyber security stops these attacks. Self-Learning AI learns the who, what, when, and where of every email user’s communication patterns. This evolving and multi-dimensional understanding allows the AI to spot subtle signs of a social engineering attack, regardless of whether it is known or novel and regardless of the tactics in place.
If an employee’s credentials are used as part of a social engineering hack, Darktrace can identify the hacker’s malicious behavior. It then makes micro-decisions to neutralize the attack within seconds, stopping the offending message without disruption to the business.
“Darktrace’s AI-powered email security solution has reduced our email threats – such as spear phishing and spoofing – by 95% because it takes autonomous action to contain malicious emails before they reach a user. We can’t expect humans to spot the difference between a real and a fake anymore – it’s not sustainable,” said Djokosoetono.
More recently, social engineering has gone beyond email, and to other platforms like Slack and Microsoft Teams. This can be more difficult for security teams to manage. Darktrace takes a holistic approach to security and can be installed anywhere an organization has data. The various coverage areas are united through the Self-Learning AI, which looks at every area of the digital estate to reveal the full scope of an attack, even as the attacker traverses multiple digital environments.
“For our employees, a weight is lifted from their shoulders,” said Djokosoetono. “When it comes to something like phishing emails, training on how to spot these is important but we simply cannot put the onus on humans to spot these well-researched, targeted email attacks. With AI in place, we’re stopping these threats before humans have to deal with them."
Darktrace’s AI is always-on and works at machine-speed to protect companies, so employees can focus on producing their best work without the constant fear of malicious messaging.
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.
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“I wonder if running that tool influenced the connectivity in some way.”
“I might need to target down or reboot, but first, I'll investigate the network using ARP. I wonder if ARP is responding properly. If I see "ip neigh stale," that could indicate a problem. I think arping might help in this situation, but I’ll need to keep an eye on how the network is behaving. It's all about figuring out where the issue lies!”
図10：エージェントの異常なLDAPアクティビティに対してトリガーされたこのLinuxサーバーに対するモデル検知は、Cyber AI Analystによって自律的に調査され、その調査結果にはエージェントの異常なSMBセッションアクティビティに関する内容が含まれ、Cyber AIAnalystインシデントに記録されました。
DarktraceのCyber AI Analystは、エージェントのアクティビティによってトリガーされたモデル検知を自律的に調査し、その調査結果を1つの重要なインシデントレポートにまとめました。インシデント報告書の内容は、エージェントによるネットワークスキャンから始まりコーディング演習内容のSMBベースの上書きで終わる、エージェントの行動の各段階を詳しくカバーしています。
図20：Cyber AI Analystは、モデル検知に対する自律的な調査を通じて得られた所見をつなぎ合わせ、エージェントの進行状況のタイムラインを作成し、アクティビティを視覚的に表したグラフとともに提供しました。
Cyber Verification Program下のAnthropic Opus 4.6モデルなど、他のフロンティアモデルを使用したエージェントも、Darktraceのシミュレートされた環境で同じ設定とタスクを使ってテストされました。反復の度に、エージェントは演習の内容または採点プログラムを変更して不正を行おうとしました。基盤となるモデルに関係なく、エージェントは自分が置かれた環境を侵害することで、100％のスコアを達成する方法を見つけることに成功していました。これらのエージェントによるハッキングは、アクティビティの内容こそ違っていましたが、すべてその環境のベースラインの振る舞いから大きく逸脱した動作を引き起こしていました。これらの逸脱はDarktraceプラットフォームに十分な検知の機会を提供し、エージェントの逃げ場はありませんでした。
エージェンティックハーネスは会話履歴をローカルに保存しますが、ダークトレースの研究者たちは、保存されたAIの応答が本当にモデルによって生成されたものであるかどうかの検証が行われていないことを発見しました。また、この設計上の選択がAnthropic Claude Code、AWS Kiro-CLI、OpenAI Codex、およびオープンソースのPiにわたって共通していることを確認しました。
会話履歴は多くの場合クライアント側に保存されます。例えば、Anthropic Claude Code、OpenAI Codex、AWS Kiro-CLI、Piなどでもそうです。そのため、ユーザーはセッションを自由に再開でき、一部の製品にはその履歴を操作する機能が組み込まれています。たとえば、会話の中の特定の時点に戻り、送信したメッセージを編集して、会話を別の軌道へ進めていくことができます。きわめて重要な点として、私たちが調査したすべてのケースにおいて、保存されているAIの応答が対応するモデルから生成されたものであり改ざんされていないことの検証は行われていませんでした。
