7 matches found
CVE-2026-5072
A bitwise shift vulnerability in Zephyr's PTP subsystem allows a remote attacker to cause undefined behavior and potential system crashes. An attacker sends a crafted PTPMSGMANAGEMENT message to set an unvalidated negative logannounceinterval value in the port's data set. When a subsequent...
CVE-2026-5072
A bitwise shift vulnerability in Zephyr's PTP subsystem allows a remote attacker to cause undefined behavior and potential system crashes. An attacker sends a crafted PTPMSGMANAGEMENT message to set an unvalidated negative logannounceinterval value in the port's data set. When a subsequent...
EUVD-2026-31413
A bitwise shift vulnerability in Zephyr's PTP subsystem allows a remote attacker to cause undefined behavior and potential system crashes. An attacker sends a crafted PTPMSGMANAGEMENT message to set an unvalidated negative logannounceinterval value in the port's data set. When a subsequent...
CVE-2026-5072
A bitwise shift vulnerability exists in the Zephyr real-time operating system (RTOS) within its PTP subsystem . A remote attacker can send a crafted PTP_MSG_MANAGEMENT message to set an unvalidated negative log_announce_interval value. When a subsequent PTP_MSG_ANNOUNCE message is processed, the ...
CVE-2026-5072 ptp: Potential Denial of Service via PTP Interval Shift
A bitwise shift vulnerability in Zephyr's PTP subsystem allows a remote attacker to cause undefined behavior and potential system crashes. An attacker sends a crafted PTPMSGMANAGEMENT message to set an unvalidated negative logannounceinterval value in the port's data set. When a subsequent...
PT-2026-42731
A bitwise shift vulnerability in Zephyr's PTP subsystem allows a remote attacker to cause undefined behavior and potential system crashes. An attacker sends a crafted PTP MSG MANAGEMENT message to set an unvalidated negative log announce interval value in the port's data set. When a subsequent PT...
Probing the Robustness of Large Language Models Safety to Latent Perturbations
Safety alignment is a key requirement for building reliable Artificial General Intelligence. Despite significant advances in safety alignment, we observe that minor latent shifts can still trigger unsafe responses in aligned models. We argue that this stems from the shallow nature of existing...