NEWSCloudsineAI’s TraceCtrl LLM Guards has been approved for the IMDA Spark programme
TraceCtrlTraceCtrl

Scan your agent attack surface.
Prove what’s exploitable.

TraceCtrl Red Teaming attacks your actual agents the way an adversary would. The TAGAAI attack graph chains individual findings into the paths that reach real data, and hands you the evidence.

Every finding looks minor on its own.
Together they’re an exploit.

An agent is not one thing to test. It is a system of prompts, tools and data stores working together, and the dangerous failures live in the combinations. A prompt injection that steers one agent, a tool with more scope than it needs, an egress channel nobody flagged: each looks minor on its own review, and together they are a working exploit. Scanners grade these findings one at a time, so the list gets long and the real path stays invisible.

TraceCtrl Red Teaming attacks your live agents the way an adversary would, finds the paths that actually reach something, and hands you the evidence to prove it.

What this changes for your team.

Three practical differences from a vulnerability scan.

Tested against your real agents

Every probe runs against your live topology from OTEL, not a generic benchmark model. A finding means your agent, your tools, your data.

Paths, not a pile of findings

The attack graph chains individual findings into the toxic combinations an adversary would actually walk, ranked by what they reach end to end.

Proof you can act on

Every validated path ships with the full exploit transcript and a mapped remediation, so the fix is specific and the re-test is one click.

Automated adversarial testing,
built for autonomous agents.

01

Map the reachable attack surface

The engagement starts read-only. It pulls your runtime topology from OTEL spans and your AI-SPM posture, so every probe is grounded in the agents, tools and knowledge stores you actually run. Objectives that reach a real tool or a known-weak path are dispatched first.

KEY CAPABILITIES
  • Live topology from OTEL: every subagent, tool call and knowledge store
  • AI-SPM posture threaded in as context, so known-weak paths are targeted first
  • Objectives with no reachable path are skipped, not wasted
RESEARCH

Powered by our own zero-day agentic threat research.

TVDB is our threat-intelligence database of malicious prompts and attack techniques, collected as they appear in the wild. New entries become red-team modules, so every engagement tests for attacks that are not in any public list yet.

Explore TVDB →
TVDB-2612CRITICAL
Cross-agent memory poisoning via shared vector store

A single poisoned embedding steers every downstream agent that retrieves it. No direct access to any agent required.

✓ SHIPPED AS RED-TEAM MODULE6H AFTER DISCOVERY

Prove what’s exploitable before someone else does.

Book a demo and we’ll scope the first assessment against your real agents, evidence included.