Strategic Deflection: Defending LLMs from Logit Manipulation

With the growing adoption of Large Language Models LLMs in critical areas, ensuring their security against jailbreaking attacks is paramount. While traditional defenses primarily rely on refusing malicious prompts, recent logit-level attacks have demonstrated the ability to bypass these safeguard...

Mechanistic Interpretability in the Presence of Architectural Obfuscation

Architectural obfuscation - e.g., permuting hidden-state tensors, linearly transforming embedding tables, or remapping tokens - has recently gained traction as a lightweight substitute for heavyweight cryptography in privacy-preserving large-language-model LLM inference. While recent work has sho...

Prompt Attacks Reveal Superficial Knowledge Removal in Unlearning Methods

In this work, we show that some machine unlearning methods may fail when subjected to straightforward prompt attacks. We systematically evaluate eight unlearning techniques across three model families, and employ output-based, logit-based, and probe analysis to determine to what extent supposedly...

SVAFD: a Secure and Verifiable Co-Aggregation Protocol for Federated Distillation

Secure Aggregation SA is an indispensable component of Federated Learning FL that concentrates on privacy preservation while allowing for robust aggregation. However, most SA designs rely heavily on the unrealistic assumption of homogeneous model architectures. Federated Distillation FD, which...

Malware Families Discovery Via Open-Set Recognition on Android Manifest Permissions

Malware are malicious programs that are grouped into families based on their penetration technique, source code, and other characteristics. Classifying malware programs into their respective families is essential for building effective defenses against cyber threats. Machine learning models have ...

LogIT 1.3/1.4 - Remote File Include Vulnerability

No description provided by source. source: http://www.securityfocus.com/bid/16932/info LogIT is prone to a remote file-include vulnerability. This issue is due to the application's failure to properly sanitize user-supplied input. Attackers may specify remotely hosted script files to be executed ...

Design/Logic Flaw

PHP remote file include vulnerability in logIT 1.3 and 1.4 allows remote attackers to execute arbitrary PHP code via a URL in the pg parameter. NOTE: the provenance of this information is unknown; the details are obtained solely from third party information...

CVE-2006-1099

PHP remote file include vulnerability in logIT 1.3 and 1.4 allows remote attackers to execute arbitrary PHP code via a URL in the pg parameter. NOTE: the provenance of this information is unknown; the details are obtained solely from third party information...

CVE-2006-1099

CVE-2006-1099 describes a PHP remote file inclusion vulnerability in logIT versions 1.3 and 1.4. An attacker can trigger arbitrary PHP code execution by supplying a crafted value for the pg parameter in a URL. Multiple sources (NVD, Red Hat, CVE records) corroborate the issue, with the note that ...

CVE-2006-1099: Undefined Security Weakness

PHP remote file include vulnerability in logIT 1.3 and 1.4 allows remote attackers to execute arbitrary PHP code via a URL in the pg parameter. NOTE: the provenance of this information is unknown; the details are obtained solely from third party information...

LogIT 1.31.4 - Remote File Inclusion

LogIT 1.31.4 - Remote File Inclusion source: https://www.securityfocus.com/bid/16932/info LogIT is prone to a remote file-include vulnerability. This issue is due to the application's failure to properly sanitize user-supplied input. Attackers may specify remotely hosted script files to be execut...

LogIT 1.3/1.4 - Remote File Inclusion

source: https://www.securityfocus.com/bid/16932/info LogIT is prone to a remote file-include vulnerability. This issue is due to the application's failure to properly sanitize user-supplied input. Attackers may specify remotely hosted script files to be executed in the context of the webserver...