28 matches found
Detecting Trojaned DNNs Via Spectral Regression Analysis
Modern DNNs are repeatedly fine-tuned to incorporate new data and functionality. This evolutionary workflow introduces a security risk when updated data cannot be fully trusted, as adversaries may implant Trojans during fine-tuning. We present MIST, a Trojan detection approach that analyzes how a...
Astra Linux - уязвимость в logback
A serialization vulnerability in the logback receiver component, as part of logback version 1.4.11, allows an attacker to carry out a Denial-of-Service attack by sending poisoned data...
SUSE CVE-2023-6378
A serialization vulnerability in logback receiver component part of logback version 1.4.11 allows an attacker to mount a Denial-Of-Service attack by sending poisoned data...
EUVD-2023-3212
Malicious code in bioql PyPI...
EUVD-2023-3046
Malicious code in bioql PyPI...
This Is How Your LLM Gets Compromised
Poisoned data. Malicious LoRAs. Trojan model files. AI attacks are stealthier than ever—often invisible until it’s too late. Here’s how to catch them before they catch you...
CLIP-Guided Backdoor Defense through Entropy-Based Poisoned Dataset Separation
Deep Neural Networks DNNs are susceptible to backdoor attacks, where adversaries poison training data to implant backdoor into the victim model. Current backdoor defenses on poisoned data often suffer from high computational costs or low effectiveness against advanced attacks like clean-label and...
Machine Learning Models Have a Supply Chain Problem
Powerful machine learning ML models are now readily available online, which creates exciting possibilities for users who lack the deep technical expertise or substantial computing resources needed to develop them. On the other hand, this type of open ecosystem comes with many risks. In this paper...
Where the Devil Hides: Deepfake Detectors Can No Longer Be Trusted
With the advancement of AI generative techniques, Deepfake faces have become incredibly realistic and nearly indistinguishable to the human eye. To counter this, Deepfake detectors have been developed as reliable tools for assessing face authenticity. These detectors are typically developed on De...
How to Backdoor the Knowledge Distillation
Knowledge distillation has become a cornerstone in modern machine learning systems, celebrated for its ability to transfer knowledge from a large, complex teacher model to a more efficient student model. Traditionally, this process is regarded as secure, assuming the teacher model is clean. This...
logback: serialization vulnerability in logback receiver
A flaw was found in the logback package, where it is vulnerable to a denial of service caused by a serialization flaw in the receiver component. By sending specially crafted poisoned data, a remote attacker can cause a denial of service condition...
logback: A serialization vulnerability in logback receiver
A flaw was found in the logback package. Affected versions of this package are vulnerable to Uncontrolled Resource Consumption 'Resource Exhaustion' via the logback receiver component. This flaw allows an attacker to mount a denial-of-service attack by sending poisoned data...
logback: A serialization vulnerability in logback receiver
A flaw was found in the logback package. Affected versions of this package are vulnerable to Uncontrolled Resource Consumption 'Resource Exhaustion' via the logback receiver component. This flaw allows an attacker to mount a denial-of-service attack by sending poisoned data...
logback: serialization vulnerability in logback receiver
A flaw was found in the logback package, where it is vulnerable to a denial of service caused by a serialization flaw in the receiver component. By sending specially crafted poisoned data, a remote attacker can cause a denial of service condition...
logback: A serialization vulnerability in logback receiver
A flaw was found in the logback package. Affected versions of this package are vulnerable to Uncontrolled Resource Consumption 'Resource Exhaustion' via the logback receiver component. This flaw allows an attacker to mount a denial-of-service attack by sending poisoned data...
logback: serialization vulnerability in logback receiver
A flaw was found in the logback package, where it is vulnerable to a denial of service caused by a serialization flaw in the receiver component. By sending specially crafted poisoned data, a remote attacker can cause a denial of service condition...
Poisoned Data, Malicious Manipulation: NIST Study Reveals AI Vulnerabilities
By Waqas NIST Unveils Insights on AI Vulnerabilities and Potential Threats.w This is a post from HackRead.com Read the original post: Poisoned Data, Malicious Manipulation: NIST Study Reveals AI Vulnerabilities...
OESA-2023-1946 logback security update
Logback is intended as a successor to the popular log4j project. Security Fixes: A serialization vulnerability in logback receiver component part of logback version 1.4.11 allows an attacker to mount a Denial-Of-Service attack by sending poisoned data. CVE-2023-6378 A serialization vulnerability ...
CVE-2023-6378
A flaw was found in the logback package, where it is vulnerable to a denial of service caused by a serialization flaw in the receiver component. By sending specially crafted poisoned data, a remote attacker can cause a denial of service condition. Mitigation Mitigation for this issue is either no...
GHSA-GM62-RW4G-VRC4 Logback is vulnerable to an attacker mounting a Denial-Of-Service attack by sending poisoned data
A serialization vulnerability in logback receiver component part of logback version 1.4.13, 1.3.13 and 1.2.12 allows an attacker to mount a Denial-Of-Service attack by sending poisoned data...