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Examines training-time backdoor attacks on deep generative models and defenses for detecting compromised models.
Explores automatically generating Linux seccomp filters from source code and binaries to sandbox applications and block exploitation techniques.
Shows how SQL injection and Microsoft JET vulnerabilities can turn IIS and SQL Server into remotely exploitable attack surfaces.
Explore how attackers abuse Active Directory for covert persistence and privilege escalation, and how defenders can detect and hunt these techniques.
Explains domain borrowing, a CDN-based technique for hiding command-and-control traffic from HTTPS inspection and firewall detection.
Apply reverse-engineering questions and threat modeling to compliance standards, using PCI as a case study to move beyond checkbox security.
Learn how the “bring me a diagram” approach creates conflict, and how collaborative system modeling and clearer expectations can improve organizational threat modeling.
Exposes how cross-cloud delegation flaws in smart-home IoT access control can let attackers retain or expand access to locks and other devices.
Examines how macOS extended file attributes and FAT compatibility flaws can expose kernel memory and enable attacks through crafted filesystem data.
Examines how accelerometers and gyroscopes in IoT devices can be attacked to compromise device security and user privacy, including speech recovery and keylogging.
An advanced look at HTTP/2 implementation flaws, downgrade attacks, and request smuggling techniques that expose vulnerabilities across web infrastructure.
A case study of exploiting Safari and privileged macOS WebViews through IPC and JavaScript injection to achieve sandbox escape and native code execution.
A deep dive into automated, large-scale threat hunting for IoT and ICS, from hunting-engine architecture to malware analysis, IoC generation, and attack-trend detection.
Explore how fuzzing and reverse engineering exposed vulnerabilities in macOS’s IOBluetoothFamily HCI and vendor-specific command handling.
An explainability-guided adversarial attack modifies PE features to make malware evade next-generation antivirus classifiers while preserving functionality.
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