Re-Triggering Safeguards within LLMs for Jailbreak Detection

This paper proposes a jailbreaking prompt detection method for large language models LLMs to defend against jailbreak attacks. Although recent LLMs are equipped with built-in safeguards, it remains possible to craft jailbreaking prompts that bypass them. We argue that such jailbreaking prompts ar...

Tracing the Dynamics of Refusal: Exploiting Latent Refusal Trajectories for Robust Jailbreak Detection

Representation Engineering typically relies on static refusal vectors derived from terminal representations. We move beyond this paradigm, demonstrating that refusal is a dynamic and sparse process rather than a localized outcome. Using Causal Tracing, we uncover the Refusal Trajectory-a persiste...

EUVD-2019-13873

Malware in sbrugna...

ARMOR: Aligning Secure and Safe Large Language Models Via Meticulous Reasoning

Large Language Models LLMs have demonstrated remarkable generative capabilities. However, their susceptibility to misuse has raised significant safety concerns. While post-training safety alignment methods have been widely adopted, LLMs remain vulnerable to malicious instructions that can bypass...

Test-Time Immunization: a Universal Defense Framework against Jailbreaks for (Multimodal) Large Language Models

While multimodal large language models LLMs have attracted widespread attention due to their exceptional capabilities, they remain vulnerable to jailbreak attacks. Various defense methods are proposed to defend against jailbreak attacks, however, they are often tailored to specific types of...

Bypassing Prompt Injection and Jailbreak Detection in LLM Guardrails

Large Language Models LLMs guardrail systems are designed to protect against prompt injection and jailbreak attacks. However, they remain vulnerable to evasion techniques. We demonstrate two approaches for bypassing LLM prompt injection and jailbreak detection systems via traditional character...

CVE-2019-4266

IBM Maximo Anywhere 7.6.2.0, 7.6.2.1, 7.6.3.0, and 7.6.3.1 does not have device jailbreak detection which could result in an attacker gaining sensitive information about the device. IBM X-Force ID: 160199...

CVE-2019-4266

IBM Maximo Anywhere 7.6.2.0, 7.6.2.1, 7.6.3.0, and 7.6.3.1 does not have device jailbreak detection which could result in an attacker gaining sensitive information about the device. IBM X-Force ID: 160199...

Design/Logic Flaw

IBM Maximo Anywhere 7.6.2.0, 7.6.2.1, 7.6.3.0, and 7.6.3.1 does not have device jailbreak detection which could result in an attacker gaining sensitive information about the device. IBM X-Force ID: 160199...

CVE-2019-4266

IBM Maximo Anywhere 7.6.2.0, 7.6.2.1, 7.6.3.0, and 7.6.3.1 does not have device jailbreak detection which could result in an attacker gaining sensitive information about the device. IBM X-Force ID: 160199...

Security Bulletin: IBM Maximo Anywhere does not have device jailbreak detection. (CVE-2019-4266)

Summary IBM Maximo Anywhere does not have device jailbreak detection which could result in an attacker gaining sensitive information about the device. Vulnerability Details CVEID: CVE-2019-4266 DESCRIPTION: IBM Maximo Anywhere does not have device jailbreak detection which could result in an...

Runtime Mobile Exploration: objection

objection is a runtime mobile exploration toolkit, powered by Frida . It was built with the aim of helping assess mobile applications and their security posture without the need for a jailbroken or rooted mobile device. The project’s name quite literally explains the approach as well, whereby...

[DVIA] Damn Vulnerable iOS Application

.png Damn Vulnerable iOS App DVIA is an iOS application that is damn vulnerable. Its main goal is to provide a platform to mobile security enthusiasts/professionals or students to test their iOS penetration testing skills in a legal environment. This application covers all the common...

Test your Mobile Hacking and Penetration testing Skills with Damn vulnerable iOS app

Smartphones are powerful and popular, with more than thousands of new mobile apps hitting the market everyday. Apps and mobile devices often rely on consumers' data, including private information, photos, and location, that can be vulnerable to data breaches, surveillance and real-world thieves...