Ibrahim Saud
@tektrixIndiaCompletionist
2 followers18,457 downloads7,053 copies47 likes38,393 views
11,679 detections
Filters
Last updated
All Time
Detection languages
3,760
1,874
1,586
966
944
Categories
4,878
3,246
1,529
1,303
1,122
Platforms
7,678
1,824
1,066
999
986
Products / Services
2,963
1,768
1,278
953
798
MITRE Techniques
3,615
3,555
2,488
1,474
1,186
CVEs
36
27
26
25
23
IDS Classtypes
360
113
38
24
24
IDS Protocols
315
114
93
47
10
Detects cloud service principals identified as AI agents or assistants performing sensitive API operations such as IAM policy modifications or storage configuration changes. This pattern may indicate that an AI service account has been compromised or misused to perform reconnaissance, privilege escalation, or persistence, exceeding its intended scope of operation.
Detects interpreter processes (e.g., python, node, bash) typically used for AI agents accessing sensitive system files or directories outside of defined sandbox or workspace paths. This behavior suggests potential sandbox escape or unauthorized path traversal by an AI agent.
Detects periodic, repetitive outbound HTTPS network connections from AI agent-runtime environments to domains that are not in the predefined allow-list. This behavior is consistent with C2 beaconing disguised as application API traffic, potentially indicating an AI agent has been compromised or misused for unauthorized external command communication.
Detects anomalous AI agent behavior where the agent ingests untrusted external content (e.g., tool outputs, RAG retrievals, or web fetches) and subsequently invokes high-risk or sensitive capabilities (such as shell execution, secret reading, or unauthorized network calls) within the same session. This pattern is indicative of an indirect prompt injection attack attempting to leverage the agent's internal tool-calling mechanisms for unauthorized actions.
Detects an AI agent or automated process that accesses sensitive data sources (such as vaults, databases, or documentation platforms) followed by an outbound HTTP POST request to known high-risk SaaS or web services (e.g., paste sites, file sharing, or webhook services) with a suspicious or large payload.
Detects anomalous activity where a single compromised AI agent identity attempts to connect to a high volume of internal agent, API, or RPC endpoints within a short time window. This behavior is indicative of lateral movement across an interconnected agent mesh.
Detects instances where an AI agent's output contains sensitive credential patterns such as AWS access keys, JWTs, private keys, or Bearer tokens. This rule monitors user communication, generic events, and file creation events to identify potential security compromises or unintended data leakage from the AI model.
Detects unauthorized privilege escalation for AI agent identities within an orchestration platform. The rule triggers when an AI agent account receives an IAM role change, API scope grant, or tool permission update that lacks a corresponding human-approval audit event, or occurs shortly after the agent generates logs indicating potential prompt injection or anomalous behavior.
Detects attempts to bypass AI agent safety guardrails by using obfuscated payloads (Base64/hex) or known jailbreak/roleplay trigger phrases. The rule specifically monitors sequences where an initial prompt is blocked by safety filters and is immediately followed by a structurally similar, potentially re-encoded prompt that is subsequently allowed, indicating an active filter evasion attempt.
Detects the creation of scheduled tasks, recurring jobs, or webhook subscriptions by a user identity flagged as an AI_AGENT. This activity is monitored for persistence, especially when the event lacks a descriptive context or targets external networks, suggesting potential unauthorized agent behavioral drift or malicious persistence.
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