Practical content from industry professionals on digital forensics · data recovery · cyber security · KVKK compliance.
Security teams drown in thousands of unverified scanner alerts, most of them false positives. KAOS verifies every finding with a canary, proves it with a PoC and prioritizes by proven exploitability. The cost of false positives, how verification works, safe automated remediation.
Read moreA mobile app binary is in the attacker's hands. KAOS analyzes Android APK and iOS apps: insecure storage, hardcoded secrets, weak crypto, exported components, backend exposure. The OWASP MASVS and MASTG framework, static and dynamic analysis, KVKK implications.
Read moreSmart contract bugs are irreversible and catastrophic. KAOS automatically analyzes contracts, detects classes such as reentrancy, access control and oracle manipulation, and verifies exploitability. Static and dynamic analysis, common vulnerability classes, Slither and Mythril, AI scaled auditing. It complements human review.
Read moreMost companies do not know their own exposed assets: forgotten subdomains, open panels, leaked credentials. KAOS continuously discovers external assets, fingerprints technology, finds exposures and verifies which are truly exploitable. Asset discovery, shadow IT, continuous monitoring and prioritization.
Read moreClassic vulnerability scanners flood teams with unverified false positives. KAOS continuously scans, writes exploits and verifies with canary anchors, so every reported finding is real. The difference between scanning and verified vulnerability management, the lifecycle, CVSS plus EPSS prioritization, multi agent coverage and continuous monitoring.
Read moreThree core frameworks for AI governance: the European Union AI Act with risk based obligations, the NIST AI Risk Management Framework with four functions, ISO/IEC 42001 as a certifiable management system. Alignment with ISO 27001 and data protection. Cross border reach for companies and DSET's evidence based compliance support.
Read moreThe threat model of autonomous trading bots: oracle and price manipulation, prompt injection hidden in the data feed, private key management, missing spend caps and circuit breakers, smart contract risk. Why on chain verifiability is a necessity. DSET's three axis audit: AI, web3, and infrastructure.
Read moreWhat AI red teaming is and why it differs from classic pentesting. Probabilistic target, natural language attack surface. The five stages of scoping, threat modeling, adversarial testing, verification, and reporting. Mapping to MITRE ATLAS and the NIST AI RMF. Manual and automated red teaming. The EU AI Act mandate.
Read morePrompt injection and jailbreak attacks with their techniques: direct and indirect injection, instruction override, role play, encoding obfuscation, payload splitting, multimodal and many shot attacks, system prompt extraction. Layered defense with instruction hierarchy, input isolation, spotlighting, output scanning, and least privilege. Based on OWASP LLM01 and NIST.
Read moreThe attack surface, threat model and independent auditing of tool using autonomous AI agents. Indirect prompt injection, excessive agency, tool and memory poisoning, multi agent propagation. Defense architecture based on OWASP LLM Top 10, MITRE ATLAS, NIST AI RMF and CSA. DSET's three stage evidence based agent audit method.
Read moreBuilt by DSET, KAOS is an autonomous security testing engine that uses a multi-agent AI architecture to scan for vulnerabilities, verify what it finds in a controlled way, and report only proven findings. It works alongside human experts, not instead of them.
Read moreAn honest roadmap for anyone starting a cybersecurity career in Ankara: roles, real prerequisites (networking, Linux, programming), certifications, hands-on practice (CTF, home-lab), and Ankara's public sector and defense industry advantage, through DSET Academy's field-based approach.
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