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August 18, 2020

Evil Corp's WastedLocker Ransomware Attacks Observation

Darktrace detects Evil Corp intrusions with WastedLocker ransomware. Learn how AI spotted malicious activity, from initial intrusion to data exfiltration.
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
Max Heinemeyer
Global Field CISO
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18
Aug 2020

Darktrace has recently observed several targeted intrusions associated with Evil Corp, an advanced cyber-criminal group recently in the headlines after a surge in WastedLocker ransomware cases. The group is believed to have targeted hundreds of organizations in over 40 countries, demanding ransoms of $500,000 to $1m to unlock computer files it seizes. US authorities are now offering a $5m reward for information leading to the arrest of the group’s leaders — understood to be the largest sum of money ever offered for a cyber-criminal.

Thanks to its self-learning nature, Darktrace's AI detected these intrusions without the use of any threat intelligence or static Indicators of Compromise (IoCs). This blog describes the techniques, tools and procedures used in multiple intrusions by Evil Corp – also known as TA505 or SectorJ04.

Key takeaways

  • The threat actor was reusing TTPs as well as infrastructure across multiple intrusions
  • Some infrastructure was only observed in individual intrusions
  • While most WastedLocker reports focus on the ransomware, Darktrace has observed Evil Corp conducting data exfiltration
  • The attacker used various ‘Living off the Land’ techniques for lateral movement
  • Data exfiltration and ransomware activity took place on weekends, likely to reduce response capabilities of IT teams
  • Although clearly an advanced actor, Evil Corp can be detected and stopped before encryption ensues

Evil Corp ransomware attack

Figure 1: The standard attack lifecycle observed in Evil Corp campaigns

Initial intrusion

While Evil Corp is technically sophisticated enough to choose from an array of initial intrusion methods, fake browser updates were the weapon of choice in the observed campaign. These were delivered from legitimate websites and used social engineering to convince users to download these malicious ‘updates’. Evil Corp has actually built a framework around this capability, referred to as SocGholish.

Establishing foothold / Command & Control Traffic

Darktrace detected different C2 domains being contacted after the initial infection. These domains overlap across various victims, showing that the attacker is reusing infrastructure within the same campaign. The C2 communication – comprised of thousands of connections over several days – took place over encrypted channels with valid SSL certificates. No single infected device ever beaconed to more than one C2 domain at a time.

Two example C2 domains are listed below with more details:

techgreeninc[.]com

SSL beacon details:

  • Median beacon period: 3 seconds
  • Range of periods: 1 seconds - 2.58 minutes
  • Data volume sent per connection on average: 921 Bytes

investimentosefinancas[.]com

SSL beacon details:

  • Median beacon period: 1.7 minutes
  • Range of periods: 1 seconds - 6.68 minutes
  • Data volume sent per connection on average: 935 Bytes

Certificate information:

  • Subject: CN=investimentosefinancas.com
  • Issuer: CN=Thawte RSA CA 2018,OU=www.digicert.com,O=DigiCert Inc,C=US
  • Validation status: OK

Note in particular the median beacon period, which indicates that some C2 channels were much more hands-on, whilst others possibly acted as backup channels in case the main C2 was burned or detected. It’s also interesting to see the low amount of data being transferred to the hands-on C2 domains. The actual data exfiltration took place to yet another C2 destination, intentionally separated from the hands-on intrusion C2s. All observed C2 websites were recently registered with Russian providers and are not responsive (see below).

Figure 2: The unresponsive C2 domain

Registrar: reg.ru

Created: 2020-06-29 (6 weeks ago) | Updated: 2020-07-07 (5 weeks ago)

Figure 3: Some key information relating to the C2 domain

Darktrace’s Cyber AI Platform detected this Command & Control activity via various behavioral indicators, including unusual beaconing and unusual usage of TLS (JA3).

Internal reconnaissance

In some cases, Darktrace witnessed several days of inactivity between establishing C2 and internal reconnaissance. The attackers used Advanced Port Scanner, a common IT tool, in a clear attempt to blend in with regular network activity. Several hundred IPs and dozens of popular ports were scanned at once, with tens of thousands of connections made in a short period of time.

Some key ports scanned were: 21, 22, 23, 80, 135, 139, 389, 443, 445, 1433, 3128, 3306, 3389, 4444, 4899, 5985, 5986, 8080. Darktrace detected this anomalous behavior easily as the infected devices don’t usually scan the network.

Lateral movement

Different methods of lateral movement were observed across intrusions, but also within the same intrusion, with WMI used to move between devices. Darktrace detected this by identifying when WMI usage was unusual or new for a device. An example of the lateral movement is shown below, with Darktrace detecting this as ‘New Activity’.

Figure 4: The model breach event log

PsExec was used where it already existed in the environment and Darktrace also witnessed SMB drive writes to hidden shares to copy malware, e.g.

C$ file=Programdata\[REDACTED]4rgsfdbf[REDACTED]

A malicious Powershell file was downloaded – partly shown in the screenshot below.

Figure 5: The malicious Powershell file

Accomplish mission – Data exfiltration or ransomware deployment

Evil Corp is currently best known for its WastedLocker ransomware. Whilst some of its recent intrusions have seen ransomware deployments, others have been classic cases of data exfiltration. Darktrace has not yet observed a double-threat – a case of exfiltration followed by ransomware.

The data exfiltration took place over HTTP to generic .php endpoints under the attacker’s control.

How Cyber AI Analyst reported on WastedLocker

When the first signs of anomalous activity were picked up by Darktrace’s Enterprise Immune System, Cyber AI Analyst automatically launched a full investigation and quickly provided a full overview of the overall incident. The AI Analyst continued to add more details to the ongoing incident as it evolved. There were a total of six AI Analyst incidents for the week spanning an example Evil Corp intrusion – and two of them directly covered the Evil Corp attack. In stitching together disparate security events and presenting a single narrative, Cyber AI Analyst did all the heavy lifting for human security staff, who could look at just a handful of fully-investigated incidents, instead of having to triage countless individual model breaches.

Figure 6: Cyber AI Analyst’s overview of the incident

Note how AI Analyst covers five phases of the attack lifecycle in a single incident report:

  1. Unusual Repeated Connections – Initial C2
  2. Possible HTTP Command & Control Traffic – Further C2
  3. Possible SSL Command & Control Traffic – Further C2
  4. Scanning of Multiple Devices – Internal reconnaissance with Advanced IP Scanner
  5. SMB Writes of Suspicious Files – Lateral Movement

Evil Corp rising

Every indicator suggests that this was not a case of indiscriminate ransomware, but rather highly sophisticated and targeted attacks by an advanced threat actor. With the ultimate goal of ransoming operations, the attacker moved towards the crown jewels of the organization: file servers and databases.

The organizations involved in the above analysis did not have Darktrace Antigena – Darktrace’s Autonomous Response technology – in active mode, and the threat was therefore allowed to escalate beyond its initial stages. With Antigena in full operation, the activity would have been contained at its early stages with a precise and surgical response which would have stopped the malicious behavior whilst allowing the business to operate as normal.

Despite the targeted and advanced nature of the threat, security teams are perfectly capable of detecting, investigating, and stopping the threat with Cyber AI. Darktrace was able to not only detect WastedLocker ransomware based on a series of anomalies in network traffic, but also stitch together those anomalies and investigate the incident in real time, presenting an actionable summary of the different attack stages without flooding the security team with meaningless alerts.

Learn more about Autonomous Response

Network IoCs:

IoCCommenttechgreeninc[.]comC2 domaininvestimentosefinancas[.]comC2 domain

Selected associated Darktrace model breaches:

  • Compromise / Beaconing Activity To External Rare
  • Compromise / Agent Beacon (Medium Period)
  • Compromise / Slow Beaconing Activity To External Rare
  • Compromise / Suspicious Beaconing Behaviour
  • Device / New or Unusual Remote Command Execution
  • Compromise / Beaconing Activity To External Rare
  • Compromise / Agent Beacon (Medium Period)
  • Compromise / Slow Beaconing Activity To External Rare
  • Device / New User Agent
  • Unusual Activity / Unusual Internal Connections
  • Device / Suspicious Network Scan Activity
  • Device / Network Scan
  • Device / Network Scan - Low Anomaly Score
  • Device / ICMP Address Scan
  • Anomalous Server Activity / Anomalous External Activity from Critical Network Device
  • Compromise / SSL Beaconing to Rare Destination
  • Anomalous Connection / SMB Enumeration
  • Compliance / SMB Drive Write
  • Anomalous File / Internal / Unusual SMB Script Write

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
Max Heinemeyer
Global Field CISO

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June 2, 2026

Stopping Stealth Attacks with Precision: How Núclea Prevented a Breach Without Disruption

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Núclea is a Brazilian data and technology company that supports the country’s financial system by delivering digital services exclusively to banks and financial institutions. Operating in an environment where trust, availability, and data integrity are critical, the company faces a threat landscape that has evolved rapidly—particularly with the rise of AI-driven cyberattacks.

Brazil has experienced a wave of successful cyber incidents targeting financial institutions, many of them enabled by insiders or compromised credentials. The result was a noticeable shift in attacker strategy: instead of focusing on end customers, threat actors began targeting the institutions and platforms that underpin the financial ecosystem itself.

“Attacks became far more directed and contextual,” explains Guilherme, who leads incident response within Núclea’s security platform engineering team. “They weren’t noisy or obviously malicious—they were precise, patient, and designed to blend into normal operations.”

That precision was on full display in January 2026, when Núclea faced one of the most convincing phishing attacks the team had seen.

A real attack, built on trust and context

The attack began with a seemingly routine email.

It was sent from a real Brazilian government institution, using legitimate infrastructure and valid credentials that were later confirmed to have been compromised. Núclea had an established, ongoing relationship with this organization, and the email’s language, tone, and subject matter aligned perfectly with the type of communication the recipient team handled every day.

Attached to the email was a PDF document containing content that looked entirely legitimate.

The problem? A single URL embedded inside that PDF.

“The message itself was correct. The sender was real. The context was familiar. Even the document content made sense,” Guilherme explains. “There was just one small element that didn’t belong.”

That small detail was enough to initiate a full attack chain.

What the attackers were trying to do

If clicked, the URL would have downloaded a malicious payload designed to:

  • Collect information about the user and device
  • Identify where the system was located within the financial ecosystem
  • Install remote access tools to maintain control
  • Deploy an infostealer to extract sensitive data
  • Execute anti-forensic scripts to erase traces of the intrusion

In other words, it was a carefully engineered operation designed for persistence and stealth, not immediate disruption.

The attack also employed urgency—a classic social engineering technique. When the link didn’t open as expected, employees requested assistance from the security team, insisting the document was important and needed to be accessed quickly.

This is precisely the kind of scenario where traditional security tools struggle: almost everything about the interaction is legitimate.

Where Darktrace made the difference

Instead of blocking the entire message or relying on known indicators of compromise, Darktrace focused on behavioral context.

Darktrace recognized:

  • That the sending organization was normally trusted
  • That the communication pattern matched historical behavior
  • That the PDF content itself was not suspicious

But it also identified that the URL embedded within the document deviated from established behavioral patterns.

Rather than disrupting business operations, Darktrace took precise action: it rewrote the URL, preventing the malicious download while leaving the rest of the email untouched.

“When we analyzed it afterward, it became clear how dangerous the attack would have been,” says Guilherme. “But it never progressed—because Darktrace acted at exactly the right point.”

Subsequent forensic analysis confirmed the payload’s malicious intent. The attack never succeeded.

Precision over disruption

For Núclea, this incident reinforced a critical lesson: modern attacks don’t always look malicious—they hide within normal activity.

“What stands out to me is the precision,” Guilherme says. “Darktrace doesn’t rely on big, obvious signals. It’s effective in situations that fall outside the standard patterns we all know.”

Building resilience in a high trust ecosystem

For Núclea, cybersecurity is not just a defensive measure—it’s a business enabler.

Availability failures or successful breaches in the financial ecosystem can have immediate, large-scale consequences, from financial loss to reputational damage. Preventing those outcomes protects not just Núclea, but its partners and customers as well.

“Cyber resilience means keeping the business running—even under attack,” Guilherme explains. “And that requires people, processes, and technology working together.”

As AI continues to accelerate both attacks and defenses, the role of security is evolving. Precision, behavioral understanding, and intelligent automation are no longer optional—they’re essential.

“The easy days were yesterday,” Guilherme says. “The challenges ahead are bigger. We need to be prepared—internally and with partners that help us build resilience.”

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June 1, 2026

効率化の裏にあるリスク:AI導入が製造現場にもたらす見えない脆弱性

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AIエージェントが製造業に与える影響

製造業界のセキュリティチームやIT担当者は、生産を守り、稼働時間を維持し、重要資産を保護するという絶え間ないプレッシャー下にあります。そしてAIは非常に大きなチャンスとともに、新たなサイバーリスクももたらしています。製造業全体で、AIはワークフローや意思決定に組み込まれつつあり、自律型AIエージェントが従業員やシステムに代わって行動する場面が増えています。

エージェント型システムは独立して行動できるため強力ですが、その同じ自律性がサイバーリスク、運用上のリスクも生み出します。エージェントは広範な権限を持ち、複雑なタスクの実行、意思決定、ツールや外部システムとのやり取りを、ほとんどまたは全く人間の介入なしに行うことができます。

あらかじめ定義されたタスクを実行する従来のAIモデルとは異なり、AIエージェントは高度なテクニックを使用して人間の意思決定プロセスを模倣することにより、新たな課題に動的に適応し、また自らの判断に基づいて意思決定し、アクションを実行します。彼らは業務の上では従業員のように見えますが、人間が持つ判断力、倫理観、または行動の結果に対する恐れが欠けています。これは、サイバー犯罪者によって簡単に操られる可能性があることを意味しており、OTネットワーク全体に埋め込まれたAIエージェントは、データ漏洩をはるかに超える脅威を生み出します。たとえば、BMWでは、AI は溶接プロセスのエラーの発生を識別するのに使われています。同社のスパータンバーグ(米サウスカロライナ州)の工場では、すべてのSUVフレーム上の300-400個のスタッドの溶接をAIが監視し、スタッドの配置間違いや欠陥を検知し直ちに修正します。このAIシステムが破損すれば壊滅的な品質管理問題につながる恐れがあります。

製造全体にエージェント型AIシステムを導入することについて多くのセキュリティチームはさまざまな懸念を示しています。ダークトレースの行ったAIサイバーセキュリティの現状調査では、製造業のセキュリティプロフェッショナルの78%が従業員によるAIエージェントの利用に懸念を抱いており、これは彼らの最も大きな危惧でした。それに続く問題点が従業員によるCopilotやChatGPT等の生成AIツールの使用であり、製造業のセキュリティプロフェッショナルの76%が懸念を抱いていました。これらのツールがますます多くのビジネスデータやプロセスにアクセスし、組織内でより多くの自律性を持つようになるにつれ、エージェントのアクティビティがほとんど可視化されていない現在、セキュリティチームにおいては機密データの露出(60%)や偶発的なポリシーおよび規制違反(59%)への懸念が高まっています。

外部からのAIによる脅威も急激に進化

製造業を変革しているのと同じAIの能力が、サイバー攻撃の形も変貌させています。

AIにより攻撃者は偵察を自動化し、標的をより高度に絞り込み、リアルタイムで適応できるようになっています。かつては人手による作業と時間を要していたことが、今では継続的かつ大規模に実行できるようになりました。そして、製造業はすでにその影響を実感しています。当社が調査した製造業のセキュリティプロフェッショナルの76%は、すでにAIを活用した脅威の影響を受けており、90%がAIによってソーシャルエンジニアリング攻撃の成功率が高まっていると回答しています。

また、攻撃のテクニック自体も進化しています。製造業界全体で、AIを利用した攻撃の経路の多様化に対する懸念が高まっています。特にリアルタイムで進化する適応型マルウェアについて、調査対象の製造業のセキュリティプロフェッショナルの半数近く(49%)が懸念しており、これは全産業の平均よりも9%高い数値です。AIを使った適応型マルウェアに続くその他の懸念には次が含まれます:

  • 自動化された脆弱性スキャンとエクスプロイトチェイニング(48%):Anthropicの新しいMythos AIモデルにより脆弱性探索が深刻化する中で、この問題は一層差し迫ったものとなっています。
  • 超パーソナライズされたフィッシングキャンペーン(46%):フィッシングは依然としてハッカーの主力兵器の1つであり、AIによってフィッシングメールはより説得力が高く検知困難なものとなり、その効果は増幅されました。

これは単に攻撃の量の増加だけでなく、攻撃の展開につれて静的な防御が対応できるよりも速く進化する脅威への変化なのです。

こうした認識が高まっているにもかかわらず、製造業の多くはまだこの変化に対応する準備ができていません。半数以上(51%)がAI駆動の脅威への準備が十分にできていないと回答し、AIの導入を管理する正式なポリシーを持っている組織はわずか37%でした。  

可視性、コンテキスト、およびガードレールを通じてAIのセキュリティを確保

これらの問題に対処するためにAIイノベーションを遅らせる必要はありません。それには、AIと同じスピードと規模で動作できる、これまでとは異なるアプローチのセキュリティが必要です。具体的には、製造業がAIの力を活用する上で、次の3つの優先課題が浮上しています。

可視性はすべての土台  

AIがどこで使用されているか、何にアクセスできるか、そしてITおよびOT環境にわたってどのように動作するかを理解する必要があります。それがなければ、リスクを測定したり管理したりすることはできません。ダークトレースの調査において、製造業のセキュリティプロフェッショナルの91%が、AIを信頼する前に、それがどのように意思決定を行うかを理解する必要があると回答したのは当然のことです。OT環境においてこのことはさらに重要です。稼働の中断は安全や環境、財務、および評判に大きな影響を及ぼすからです。

可視性をアクションにつなげるにはコンテキストが必要  

AIによって形作られる環境において、正常とされる挙動は絶えず変化します。つまり、脅威を検知するにはビヘイビアベースのアプローチが必要なのです。組織全体で生活パターンを理解し、わずかな逸脱をリアルタイムに検知すること- これは従来のセキュリティとリスク管理に対するアプローチからの根本的な変化です。

エージェントからの露出を防ぐガードレール  

AIシステムがより大きな責任を担うようになるなかで、組織はAIが何をできるか、そしていつ独立して行動できるかについて、明確な境界を設ける必要があります。これらのコントロールは何かがあってから適用されるのではなく、システム自体に組み込んでおかなければなりません。  

製造業のITおよびOT環境におけるAIエージェントのセキュリティ

エージェント型AIの出現は製造業を変革し、次世代のオペレーションを支える一方で、脅威ランドスケープも一変させています。これは単なる脅威の増加ではなく、自律型システムへの移行、挙動の絶え間ない変化、そしてマシンスピードで進行するリスクです。AIを活用しつつリスクを管理するという課題に取り組む組織にとって、可視性、コンテキスト、ガードレールはセキュリティの基盤となります。

Darktraceはこの基盤を実現することにより、製造業の安全なAIアプローチ構築を支援します。ITおよびOT環境全体を可視化し、異常なアクティビティに対するリアルタイムの検知および対応を提供することにより、従業員が使用するプロンプトや構築するエージェントから、それらのエージェントの環境全体での動作に至るまで、AIアクティビティの理解を可能にします。これにより、AIの導入を拡大する製造業はコントロールを犠牲にすることなくイノベーションの基盤を構築することができます。

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Dr. Oakley Cox-Robinson
Senior Director of Product
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