443 matches found
EUVD-2006-6914
Malware in sbrugna...
EUVD-2018-10608
Malware in sbrugna...
EUVD-2006-3375
Malware in sbrugna...
EUVD-2014-7137
Malware in sbrugna...
EUVD-2012-5992
Malware in sbrugna...
EUVD-2015-7588
Malware in sbrugna...
EUVD-2022-5585
Malicious code in bioql PyPI...
EUVD-2023-42105
Malicious code in bioql PyPI...
EUVD-2022-3436
Malicious code in bioql PyPI...
EUVD-2022-2784
Malicious code in bioql PyPI...
EUVD-2022-3399
Malicious code in bioql PyPI...
EUVD-2023-33958
Malicious code in bioql PyPI...
EUVD-2022-43490
Malicious code in bioql PyPI...
Inefficient Algorithmic Complexity
Overview Affected versions of this package are vulnerable to Inefficient Algorithmic Complexity due to an inefficient algorithmic complexity issue in the mjson parsing library when analyzing JSON content, such as with the jsonquery or jwtpayloadquery function. An attacker can cause resource...
The vulnerability of the Transport Layer Security library GnuTLS, related to its algorithmic complexity, allows attackers to induce a service failure.
The vulnerability of the Transport Layer Security library GnuTLS is related to its algorithmic complexity. Exploiting this vulnerability could allow a malicious actor to cause service failures...
Linux Distros Unpatched Vulnerability : CVE-2017-11343
The Linux/Unix host has one or more packages installed that are impacted by a vulnerability without a vendor supplied patch available. - Due to an incomplete fix for CVE-2012-6125, all versions of CHICKEN Scheme up to and including 4.12.0 are vulnerable to an algorithmic complexity attack. An...
Fairness and Bias in Algorithmic Hiring: a Multidisciplinary Survey
Employers are adopting algorithmic hiring technology throughout the recruitment pipeline. Algorithmic fairness is especially applicable in this domain due to its high stakes and structural inequalities. Unfortunately, most work in this space provides partial treatment, often constrained by two...
Navigating the Deep: Signature Extraction on Deep Neural Networks
Neural network model extraction has emerged in recent years as an important security concern, as adversaries attempt to recover a network's parameters via black-box queries. A key step in this process is signature extraction, which aims to recover the absolute values of the network's weights laye...
The Ephemeral Threat: Assessing the Security of Algorithmic Trading Systems Powered by Deep Learning
We study the security of stock price forecasting using Deep Learning DL in computational finance. Despite abundant prior research on the vulnerability of DL to adversarial perturbations, such work has hitherto hardly addressed practical adversarial threat models in the context of DL-powered...
Exploring PLeak: An Algorithmic Method for System Prompt Leakage
What is PLeak, and what are the risks associated with it? We explored this algorithmic technique and how it can be used to jailbreak LLMs, which could be leveraged by threat actors to manipulate systems and steal sensitive data...