AI Risk Wire

Cases › security breach › LR-2026-0610

Hacker uses DeepSeek agent to autonomously attack vulnerable servers

Confirmed Why: 3 independent outlets · 3 independent reports

Status: advice only, no fix reported

Severity moderate
Reported 31 Jul 2026
Developer and model DeepSeek
Agent tool Hermes Agent
Could do operating system terminals, running commands, internet connection

No source states: loss or records, deployer, industry.

Severity moderate: test met: data and systems of others were touched, and the scope is bounded to three confirmed compromises

A Chinese-speaking threat actor used the DeepSeek model inside the open-source Hermes Agent framework to run offensive operations against internet-exposed systems. After an initial operator task, the agent searched for targets, downloaded public exploits and attempted attacks on Langflow and n8n. Those attempts failed because the exposed systems did not meet the exploits' requirements. The same operator conducted separate manual attacks on more than 460 systems, with three confirmed compromises. Hermes accidentally started a web server from its home directory, exposing the operator's keys, exploit scripts, target lists and logs. Palo Alto Networks' Unit 42 discovered the activity and reported it on 2026-07-31.

What happened

1 · What went wrongAttacks on Langflow and n8n failed because the exposed systems did not meet the exploits' configuration requirements.
2 · What it reached or didUnit 42 confirmed three successful compromises across roughly 460 attempted targets.
3 · How it was caughtUnit 42 discovered the activity after Hermes accidentally exposed the attacker's environment through a web server.

What was done

Advice in source, not a fix by the party

“Organizations should patch exposed Langflow, n8n and Marimo systems, along with customer-managed NetScaler ADC or Gateway appliances configured as Security Assertion Markup Language (SAML) identity providers.”

Known flaws patched

Risks

AI used to run a cyber attack
Primary
96 incidents
Rising: 24 vs 4.0 a week

Read from the sources; not yet reviewed by a person.

Controls

Application

Did not exist Human approval for high-impact actions

Control failure chain

L1 · Model Not stated in sourcesDeepSeek
L2 · Harness Not stated in sourcesHermes Agent
L3 · Application Attacker's ownThe attacker
L4 · Infrastructure / target Not stated in sourcesOrganisation hit

L1 · ModelDeepSeekModel provider

No source mentions a control at this layer.

Model version not linked to a model card.

Other controls for this risk at this layer, not mentioned in the sources: Safety training and refusal, Cyber and weapons safeguards, Abuse monitoring and account enforcement, Staged or restricted release, Dangerous-capability testing before release, Outside red-teaming, Content safety classifiers, Safeguards kept on in testing, Reasoning monitoring.

L2 · HarnessHermes AgentAgent framework vendor

No source mentions a control at this layer.

L3 · ApplicationThe attackerDeployer

The attacker ran the agent; this layer was the attacker's own.

L4 · Infrastructure / targetOrganisation hit

No source mentions a control at this layer.

Other controls for this risk at this layer, not mentioned in the sources: Known flaws patched, Multi-factor sign-in and password policy, Network segmentation, Intrusion and endpoint detection, Backups and recovery, Phishing and fraud filters.

EffectiveNot effectiveNot effective (bypassed)Did not existNot stated in sourcesNot yet checkedAttacker's ownOrder: model · harness · application · target

Controls for this risk: result in this incident

ControlPart of the systemResult
Content safety classifiersL1 ModelNot stated in sources
Safety training and refusalL1 ModelNot stated in sources
Cyber and weapons safeguardsL1 ModelNot stated in sources
Dangerous-capability testing before releaseL1 ModelNot stated in sources
Outside red-teamingL1 ModelNot stated in sources
Staged or restricted releaseL1 ModelNot stated in sources
Abuse monitoring and account enforcementL1 ModelNot stated in sources
Reasoning monitoringL1 ModelNot stated in sources
Safeguards kept on in testingL1 ModelNot stated in sources
Human approval for high-impact actionsL3 ApplicationDid not exist
Known flaws patchedL4 Infrastructure / targetNot stated in sources
Multi-factor sign-in and password policyL4 Infrastructure / targetNot stated in sources
Network segmentationL4 Infrastructure / targetNot stated in sources
Intrusion and endpoint detectionL4 Infrastructure / targetNot stated in sources
Backups and recoveryL4 Infrastructure / targetNot stated in sources
Phishing and fraud filtersL4 Infrastructure / targetNot stated in sources

Similar incidents

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Evidence

No source states: what the AI was doing, when it was found, how many records were exposed, the direct loss, a count of the other parties affected, any court case, the cause, what set it off, what was done.

Show the full account: 5 items from the primary sources

What happened, in order

  1. 2026-05 In a recovered session, the agent downloaded a Langflow exploit and enumerated 84 instances.

Not dated in the sources:

  • Earlier, a separate Hermes-linked incident exposed details of an alleged attack against Thailand's Ministry of Finance.
  • The Langflow attack stopped because the target lacked auto_login and a usable public flow identifier.
  • Hermes started an unintended HTTP server from /home/worker, exposing the operation.
  • Palo Alto Networks' Unit 42 discovered the activity.
Show every field, with its source and grade

The AI system

Model
DeepSeek
C one secondary source states it
Software around the model
Hermes Agent
C one secondary source states it
Tools it was given
operating system terminals, running commands, internet connection
C one secondary source states it
How much it acted alone
it acted alone, unwatched
C one secondary source states it
State of its safeguards
loosened local safeguards
C one secondary source states it

What happened

When it happened
2026-05-01
C one secondary source states it
Earliest source we hold
2026-07-31
D inferred by us from the described behaviour, reason shown
Who caught it
an outside party
C one secondary source states it
Cause in detail
Yolo mode let the agent execute risky commands without first requesting operator permission
C one secondary source states it
Who caused it
an outside attacker
C one secondary source states it
Where its input came from
Instructions from a Telegram channel
C one secondary source states it
Earlier warning signs
Earlier Hermes-linked incident exposing an alleged cyberattack against Thailand's Ministry of Finance
C one secondary source states it
What went wrong
security breach
C one secondary source states it
AI agent
an AI agent acted
C one secondary source states it
primary risk
RK07
D inferred by us from the described behaviour, reason shown
secondary risks
RK02
D inferred by us from the described behaviour, reason shown
control chain
layer: L3; party: attacker; control id: B1; outcome: missing; quote: The agent supports a "Yolo" mode that allows it to operate and execute commands, even risky ones, without first requesting permission from its operator.; source index: 0
C one secondary source states it
remediations
kind: advice; controls added: J1; quote: Organizations should patch exposed Langflow, n8n and Marimo systems, along with customer-managed NetScaler ADC or Gateway appliances configured as Security Assertion Markup Language (SAML) identity providers.; source index: 1
C one secondary source states it

Impact

Severity
moderate
D inferred by us from the described behaviour, reason shown
Kind of harm
others' security
C one secondary source states it
Who was affected
Three confirmed compromises: memory data exfiltration from Citrix NetScaler and suspected session hijacking against a Malaysian government entity
C one secondary source states it
Why this severity
test met: data and systems of others were touched, and the scope is bounded to three confirmed compromises
D inferred by us from the described behaviour, reason shown

Notes on gaps

Discovery date is not stated; the occurrence is known only as a May 2026 session.

LR-2026-0610 · version 1 · published 2026-11-01 after automatic checks; not yet checked field by field by a person · JSON