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Threat actor

C3 AI

Last fetched

C3 AI is a threat actor tracked in WhisperGraph's MITRE ATT&CK corpus, observed using 0 techniques.

Description

C3 AI, founded by billionaire Tom Siebel, develops law enforcement surveillance technologies distributed through Project Sherlock, a $12 million AI-powered surveillance system developed for the San Mateo County Sheriff's Office. The project was designed to unify data streams from at least 15-16 different police agencies, integrating information from license plate readers, surveillance cameras, and arrest records into a single AI-powered application. The system has been plagued by technical problems, including data security issues where the software was found to be ingesting "restricted cases" that should only have been visible to select individuals. Despite these local law enforcement struggles, C3 AI has secured significantly larger government contracts, most notably a five-year, $500 million agreement with the U.S. Department of Defense. It counts Amazon Web Service as a longtime partner, and also works closely with Google Cloud.

Techniques by tactic

No ATT&CK techniques are recorded for C3 AI in WhisperGraph.

Attributed infrastructure

None published. WhisperGraph carries no ATTRIBUTED_TO edge to C3 AI today — this states the absence of a published link, not that C3 AI has no infrastructure.

References

© The MITRE Corporation. This work is reproduced and distributed with the permission of The MITRE Corporation.

Related pages

Pivot from C3 AI into its techniques, tactics and any attributed infrastructure.

Queries

Resolves the slug to this actor, merging every duplicate node sharing the same name.


MATCH (a:ACTOR)
WHERE a.name =~ $pattern OR any(x IN a.aliases WHERE x =~ $pattern)
RETURN a.id AS id, a.name AS name, a.aliases AS aliases, a.description AS description,
       a.references AS references, a.campaigns AS campaigns
LIMIT 25
Run yourself →

Techniques this actor uses, grouped by the tactic each one serves.


MATCH (a:ACTOR {name: $name})-[:USES_TECHNIQUE]->(t:ATTACK_PATTERN)
OPTIONAL MATCH (t)-[:USES_TACTIC]->(tac:ATTACK_PATTERN)
RETURN t.id AS techniqueId, t.name AS techniqueName, tac.id AS tacticId, tac.name AS tacticName
LIMIT 1000
Run yourself →

Infrastructure publicly attributed to this actor.


MATCH (n)-[:ATTRIBUTED_TO]->(a:ACTOR {name: $name})
RETURN labels(n)[0] AS kind, n.name AS name
LIMIT 25
Run yourself →

Or query Whisper from your own LLM workflow via the Whisper MCP server.