A fixed-scope security engagement that tests and hardens AI agents before they can expose data, credentials, code, or financial accounts.
Added Jul 30, 2026
Medium opportunity (67%)
Organizations are connecting AI agents to source code, credentials, internal data, digital wallets, and operational systems faster than their security teams can evaluate the resulting attack paths. Model guardrails alone are unreliable because attackers can use prompt injection, switch models, impersonate authorized users, or exploit overly broad tool permissions. Buyers need to know what each agent can access, what damage it can cause, and which controls will contain a failure.
Offer a fixed-scope assessment that inventories an agent's tools, credentials, data access, network reach, and approval rules, then tests realistic prompt-injection, impersonation, data-exfiltration, and unauthorized-action scenarios. Deliver a prioritized remediation plan and implement practical controls such as sandboxing, least-privilege credentials, transaction limits, human approval gates, logging, and emergency revocation. Begin as an expert-led service and productize repeatable test protocols and evidence collection over time.
Commercial and open-weight AI models are lowering the skill and time required for attacks while organizations are granting agents permission to act on sensitive systems. The signals also indicate that new models can be jailbroken quickly, making predeployment and recurring control testing more urgent than reliance on provider guardrails.
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Secure AI-powered products. Evaluate risks such as prompt injection, unsafe tool use, identity and delegation failures, excessive agency, data exposure, tenant isolation, and sandbox escapes. Threat model new capabilities. Identify trust boundaries, abuse cases, and high-impact failure modes before implementation. Translate findings into practical, prioritized mitigations.
Design and implement security controls for agentic and AI-assisted workflows, building guardrails to mitigate risks such as prompt injection, data exfiltration, and misuse of developer and system privileges
Build identity controls, sandboxes, and safety harnesses that let services and AI agents operate with least privilege, constrained actions, clear auditability, and effective monitoring
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