How a frontier AI company boosted agent security by 38% through red teaming

The company needed an independent, large-scale red team exercise to ensure their agents were safe before public release. Testing had to go beyond traditional penetration audits and cover AI-specific threats such as prompt injection, tool misuse, and multi-step exploit chains—while still preserving agent functionality for legitimate business tasks.

• Validate resilience against prompt injection and indirect attacks
• Ensure safe tool use and prevent data exfiltration
• Test both single-turn exploits and multi-step adversarial chains
• Establish monitoring protocols and remediation playbooks

The in-house security team lacked the scale and diversity of attack strategies needed to test sophisticated AI agents. Competitor breaches had raised client expectations, putting additional pressure on the company to deliver measurable assurance.

• In-house team of 4 engineers covered just 24% of attack surface
• Traditional penetration testing missed 64% of AI-specific vulnerabilities
• Security scanners produced 71% false negatives on agent exploits
• Previous audits found only 40% of vulnerabilities later confirmed in the wild
• Lack of diverse perspectives left 55% of attack vectors untested
• Customer security requirements grew 280% after high-profile industry breaches

CleverX mobilized a global team of AI security researchers, combining human creativity with systematic frameworks to probe vulnerabilities from every angle.

Expert recruitment:

• 22 specialists: 8 former pen-testers, 7 AI security researchers, 7 prompt engineers
• Avg 5 years of security research experience with documented CVEs
• Expertise spanning web security, API exploitation, and social engineering
• Distributed across 8 time zones for continuous red team coverage

Technical framework:

• Designed 1,200 attack scenarios across 40 vulnerability categories
• Built reproducible exploit chains with detailed proofs of concept
• Developed automated harness to test malicious inputs against agent responses
• Implemented severity scoring aligned with CVSS, tailored for AI agents

Quality protocols:

• Secure sandbox environments with full audit logging
• Blind testing before team collaboration to maximize discovery diversity
• Responsible disclosure process for critical findings
• 200+ pages of structured remediation documentation

The exercise progressed from setup through intensive testing to hardening validation, producing both technical improvements and stronger business confidence.

Week 1: Setup & onboarding

• Established isolated testing environment with audit controls
• Verified researcher clearances and permissions
• Deployed monitoring for safe exploit demonstrations

Weeks 2–4: Vulnerability discovery

• Tested 300 vectors daily across 12 configurations
• Discovered 145 unique vulnerabilities, 31 rated critical
• Identified 8 novel attack types absent from existing literature

Weeks 5–6: Exploit development

• Built proofs-of-concept for 89% of discovered flaws
• Demonstrated 12 attack chains bypassing existing defenses
• Quantified exposure risk covering 2.3M records

Weeks 7–8: Remediation & validation

• Verified patches for 127 vulnerabilities, cutting attack surface by 78%
• Delivered 43 detection rules for runtime monitoring
• Produced security best-practices manual for internal teams

Efficiency gains:

Testing scale and automation accelerated timelines while reducing costs.

• Cut 6-month security review into 8 weeks
• Reduced incident rates by 61% in new releases
• Lowered validation costs by $1.4M
• Accelerated patch cycles by 45%

Quality improvements:

The red team revealed deeper flaws and improved coverage versus traditional audits.

• Detected 38% more vulnerabilities than prior audits
• Achieved 94% coverage of OWASP Top 10 for LLMs
• Improved detection accuracy from 40% → 87%
• Reduced critical vulnerability escape rate to 8%

Business impact:

Security improvements had measurable financial and reputational outcomes.

• Prevented ~$3.8M in potential breach-related costs
• Secured $5.2M in government contracts through certifications
• Reduced cyber insurance premiums by 28%
• Won 4 enterprise clients citing security confidence

Strategic advantages:

The program created reusable security assets for long-term resilience.

• Established rotating red team program
• Built vulnerability database with 450 test cases
• Developed first-of-its-kind AI agent security benchmark
• Filed 2 patent applications for testing methodology

The company's program was certified by a leading cybersecurity standards body.