hackingincidents.ai
Ledger / 28 Nov 2025

AI-assisted AWS intrusion reaches admin in under 10 minutes

Strong

Sysdig infers LLM use from code style, comments and hallucinated artifacts; no model is identified.

Credentials from public S3 buckets led to Lambda code injection and rapid privilege escalation. Sysdig sees multiple signs that LLMs generated code and made real-time decisions. The attacker also invoked Bedrock models on the victim's bill.

“multiple indicators that suggest the threat actor leveraged large language models (LLMs) throughout the operation”Sysdig

Sources

Date
28 Nov 2025
Disclosed
3 Feb 2026
Actor
Unnamed actor (Serbian-language comments in injected code) (unknown), as attributed by Sysdig
Targets
One AWS customer environment (RAG data buckets, Lambda, Bedrock)
What the AI did
Recon, Exploit dev, Ops automation, LLMjacking, Agentic intrusion, Fraud
Model
unspecified LLM
Model family
Unspecified
Model basis
inferred
Autonomy
semi-autonomous
Outcome
Admin privileges in ~8 minutes, 19 AWS principals compromised, Bedrock models and GPU instances abused.