Agent Red gives security teams an AI-powered way to discover, test, verify, and re-test risk—inside boundaries you define.
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TARGETlearnmore.ly
LAST SCAN2026-04-12 11:21:09
ACTIVE FINDINGS7STATUS
idle · readyENGAGEMENTAR-2026-04-12-LMOperational status across all modules
us-easteu-westap-southedge-01edge-02
Agent stream247,128/ 500,000 tokens
Modules
Debuggable flag enabled on production APK
WeaponizedMobile · Tawajah4m agoServer-Side Request Forgery (SSRF) in custom endpoints
Known CVERepo · Agent-Slayer12m agoHardcoded API keys in Flutter kernel_blob.bin
Publicly exploitableMobile · Tawajah21m agoPublicly accessible staging environments
Internet exposedPentest · learnmore.ly1h agoFTP service exposed on default port (21)
Pentest · learnmore.ly1h agoThe problem
Applications change continuously. Infrastructure changes continuously. Attack techniques change continuously.
But security assessments are still often periodic and heavily manual.
One platform
Follow risk across every surface from one controlled environment.
Application and API penetration testing across the paths attackers actually use.
AI-assisted security review that follows risk across code, dependencies, and CI/CD.
Cloud posture and misconfiguration assessment across AWS, Google Cloud, and hosts reached over SSH.
Static and dynamic mobile security analysis aligned to real application behavior.
Agent orchestration
A staged workflow keeps every action purposeful, reviewable, and inside the engagement scope.
Delegates, coordinates, and preserves the rules of engagement.
VERIFY BEFORE REPORT Important findings move through independent validation before they reach your team.
Control before automation
AI operates inside the rules. Your security team defines the rules.
Every action stays within the authorized target boundary.
Material findings are checked before they become reports.
One view across findings, evidence, and remediation.
Confirm that a fix worked instead of assuming it did.
Evidence, not just a concept
Different technologies. Different attack surfaces. Different classes of vulnerabilities.
AI / LLM security framework
Agent Red traced risk from prompt injection into the surrounding application architecture, including path traversal, stored XSS, and secrets exposure.
ALAF is deliberately vulnerable; this was a coverage and capability validation case.
Kali Linux privacy tool
The review found unsafe destructive file operations and a silent configuration error that could leave intended browser protections inactive.
Both high-severity findings were independently verified by Agent Red’s verifier.
Open-source OSINT platform
The assessment followed critical paths into CI/CD supply-chain exposure and argument injection—not just the application’s primary code paths.
Coverage tracking reported 37/37 files reviewed; critical findings were sent to verification.
Finding something is not enough
Start controlled
Agent Red is currently positioned for structured pilots and controlled use under an agreed scope.
Choose a limited set of authorized systems or repositories.
Agree scope, exclusions, permissions, and testing windows.
Run Agent Red under your security team’s supervision.
Examine findings, evidence, and false positives together.
Fix selected findings and verify the remediation.
Measure coverage, quality, speed, and operational value.
