A Synthetic Conversational Smishing Dataset for Social Engineering Detection

Smishing SMS phishing has become a serious cybersecurity threat, especially for elderly and cyber-unaware individuals, causing financial loss and undermining user trust. Although prior work has focused on detecting smishing at the level of individual messages, real-world attackers often rely on...

Benchmarking Machine Learning Models for IoT Malware Detection under Data Scarcity and Drift

The rapid expansion of the Internet of Things IoT in domains such as smart cities, transportation, and industrial systems has heightened the urgency of addressing their security vulnerabilities. IoT devices often operate under limited computational resources, lack robust physical safeguards, and...

AI-Powered Hybrid Intrusion Detection Framework for Cloud Security Using Novel Metaheuristic Optimization

Cybersecurity poses considerable problems to Cloud Computing CC, especially regarding Intrusion Detection Systems IDSs, facing difficulties with skewed datasets and suboptimal classification model performance. This study presents the Hybrid Intrusion Detection System HyIDS, an innovative IDS that...

How Worrying Are Privacy Attacks against Machine Learning?

In several jurisdictions, the regulatory framework on the release and sharing of personal data is being extended to machine learning ML. The implicit assumption is that disclosing a trained ML model entails a privacy risk for any personal data used in training comparable to directly releasing tho...

Picklescan is missing detection when calling built-in python cProfile.runctx

Summary Using cProfile.runctx function, which is a built-in python library function to execute remote pickle file. Details The attack payload executes in the following steps: First, the attacker craft the payload by calling to cProfile.runctx function in reduce method Then when the victim after...

Picklescan is missing detection when calling built-in python doctest.debug_script

Summary Using doctest.debugscript function, which is a built-in python library function to execute remote pickle file. Details The attack payload executes in the following steps: First, the attacker craft the payload by calling to doctest.debugscript function in reduce method Then when the victim...

GHSA-FQQ6-7VQF-W3FG Picklescan is missing detection when calling built-in python doctest.debug_script

Summary Using doctest.debugscript function, which is a built-in python library function to execute remote pickle file. Details The attack payload executes in the following steps: First, the attacker craft the payload by calling to doctest.debugscript function in reduce method Then when the victim...

Picklescan is missing detection when calling built-in python idlelib.pyshell.ModifiedInterpreter.runcode

Summary Using idlelib.pyshell.ModifiedInterpreter.runcode function, which is a built-in python library function to execute remote pickle file. Details The attack payload executes in the following steps: First, the attacker craft the payload by calling to idlelib.pyshell.ModifiedInterpreter.runcod...

Picklescan is missing detection when calling built-in python lib2to3.pgen2.pgen.ParserGenerator.make_label

Summary Using lib2to3.pgen2.pgen.ParserGenerator.makelabel function, which is a built-in python library function to execute remote pickle file. Details The attack payload executes in the following steps: First, the attacker craft the payload by calling to...

Picklescan has a missing detection when calling built-in python library idlelib.calltip.get_entity

Summary Using idlelib.calltip.getentity function, which is a built-in python library function to execute remote pickle file. Details The attack payload executes in the following steps: First, the attacker craft the payload by calling to idlelib.calltip.getentity function in reduce method Then whe...

GHSA-7CQ8-MJ8X-J263 Picklescan has a missing detection when calling built-in python idlelib.autocomplete.AutoComplete.fetch_completions

Summary Using idlelib.autocomplete.AutoComplete.fetchcompletions, which is a built-in python library function to execute remote pickle file. Details The attack payload executes in the following steps: First, the attacker craft the payload by calling to...

Picklescan has a missing detection when calling built-in python idlelib.autocomplete.AutoComplete.get_entity

Summary Using idlelib.autocomplete.AutoComplete.getentity, which is a built-in python library function to execute remote pickle file. Details The attack payload executes in the following steps: First, the attacker craft the payload by calling to idlelib.autocomplete.AutoComplete.getentity functio...

Picklescan has a missing detection when calling built-in python profile.Profile.run

Summary Using profile.Profile.run, which is a built-in python library function to execute remote pickle file. Details The attack payload executes in the following steps: First, the attacker craft the payload by calling to profile.Profile.run function in reduce method Then when the victim after...

Picklescan missing detection when calling pytorch function torch.jit.unsupported_tensor_ops.execWrapper

Summary Using torch.jit.unsupportedtensorops.execWrapper function, which is a pytorch library function to execute remote pickle file. Details The attack payload executes in the following steps: First, the attacker craft the payload by calling to torch.jit.unsupportedtensorops.execWrapper function...

Google Adds Multi-Layered Defenses to Secure GenAI from Prompt Injection Attacks

Google has revealed the various safety measures that are being incorporated into its generative artificial intelligence AI systems to mitigate emerging attack vectors like indirect prompt injections and improve the overall security posture for agentic AI systems. "Unlike direct prompt injections,...

CVE-2019-8760

This issue was addressed by improving Face ID machine learning models. This issue is fixed in iOS 13. A 3D model constructed to look like the enrolled user may authenticate via Face ID...

Detecting Quishing Attacks with Machine Learning Techniques through QR Code Analysis

The rise of QR code based phishing "Quishing" poses a growing cybersecurity threat, as attackers increasingly exploit QR codes to bypass traditional phishing defenses. Existing detection methods predominantly focus on URL analysis, which requires the extraction of the QR code payload, and may...

Development of an Adapter for Analyzing and Protecting Machine Learning Models from Competitive Activity in the Networks Services

Due to the increasing number of tasks that are solved on remote servers, identifying and classifying traffic is an important task to reduce the load on the server. There are various methods for classifying traffic. This paper discusses machine learning models for solving this problem. However, su...

FLARE: Feature-Based Lightweight Aggregation for Robust Evaluation of IoT Intrusion Detection

The proliferation of Internet of Things IoT devices has expanded the attack surface, necessitating efficient intrusion detection systems IDSs for network protection. This paper presents FLARE, a feature-based lightweight aggregation for robust evaluation of IoT intrusion detection to address the...

AIs as Trusted Third Parties

This is a truly fascinating paper: "Trusted Machine Learning Models Unlock Private Inference for Problems Currently Infeasible with Cryptography." The basic idea is that AIs can act as trusted third parties: Abstract: We often interact with untrusted parties. Prioritization of privacy can limit t...