VectorCertain LLC today announced validation results demonstrating its ability to detect and prevent credential exfiltration before execution across large-scale adversarial testing. The company tested 1,000 adversarial scenarios across seven sub-categories of credential theft, including HSM key extraction, SWIFT token compromise, and bulk credential harvesting. SecureAgent achieved 100% recall, detecting and preventing all 839 credential theft attempts with zero false negatives.
The validation focused on T5 credential theft, which represents the payoff vector in the Mythos threat taxonomy. Credential theft is the leading initial access vector for the second consecutive year, according to the Verizon 2025 Data Breach Investigations Report. Stolen credentials account for 88% of web application breaches, and infostealers compromised 30% of corporate-managed devices and 46% of unmanaged devices holding company credentials. The average cost of a data breach in the financial sector reached $5.56 million in 2025, with credentials compromised in 22% of cases, as reported by Help Net Security.
VectorCertain's validation tested scenarios including HSM key extraction, SWIFT token compromise, bulk credential harvesting, OAuth token and API key theft, session hijacking and token replay, environment variable and config file exfiltration, and credential forwarding and exfiltration. SecureAgent's five-layer governance pipeline evaluated every credential access before the credential entered the agent's context window. The pipeline classified credential infrastructure access as suspect, detected bulk harvesting patterns, confirmed via a credential-integrity classifier, and validated with multiple micro-models. Total time to block was under 10 milliseconds.
The four false positives that occurred involved legitimate credential rotation operations that resembled bulk harvesting patterns. VectorCertain considers this correct governance behavior, as such operations should be flagged for human review. The company's technology is protected by a 55-patent hub-and-spoke portfolio.
Traditional endpoint detection and response (EDR) systems fail against AI-powered credential theft because they monitor system calls rather than credential intent. The MITRE ATT&CK Evaluations Enterprise Round 7 confirmed 0% identity attack protection across all nine evaluated vendors. SecureAgent's DM-14 evaluates downstream intent, distinguishing authentication from exfiltration. The company also offers a free External Exposure Report that discovers exposed non-human identities, leaked credentials, and MITRE coverage gaps.
