In real-world cyberattacks, adversaries frequently exploit a combination of vulnerabilities, bugs, and misconfigurations to compromise systems. To systematically analyze the root causes behind these issues, the Common Weakness Enumeration (CWE) framework provides a standardized taxonomy of software weaknesses. While vulnerability databases are central to cataloging known issues, many security-relevant descriptions first appear in informal sources such as blog posts, CTI reports, and social media. Although these sources predominantly offer broader cybersecurity insights, they occasionally yield details that may indicate underlying weaknesses not captured in formal databases. We propose a two-step approach to extract these security-related descriptions from unstructured threat intelligence and automatically map them to their corresponding CWE categories. First, a binary classifier detects sentences resembling CVE descriptions, identifying information relevant to security teams. Then, we apply a self-supervised learning model to predict the most appropriate CWE, enabling structured analysis even in the absence of formal vulnerability tracking. As no ground truth exists for this task, we conduct expert-driven validation. Our results show strong performance, with an F1-score of 98.17
Mapping Common Vulnerabilities and Exposures (CVEs) to the related Common Weakness Enumerations (CWE) is crucial in cybersecurity because this link allows categorizing vulnerabilities, prioritizing remediation efforts, and improving mitigation strategies. However, this process often requires manual effort to understand and connect a CVE to its CWE, which is undesirable due to its time-consuming nature. Existing automated approaches typically rely on vectorizing CVE descriptions using embedding techniques followed by machine learning classifiers. However, little attention has been given to evaluating whether CVE descriptions are the most effective starting point for automated classification, as these descriptions often contain irrelevant details that do not contribute to CVE-to-CWE mapping. Our research investigates to what extent we can automatically extract key information from CVE descriptions required to perform such mapping and evaluates how this technique improves existing methods for identifying related weaknesses using this extracted information. To this end, we present an approach that automates extracting key terms of CVEs through Large Language Models and evaluate the effect of focusing on various parts of the CVE description. We show that our key term extraction technique improves the F1-score of transformer-based classification of CVEs into CWEs up to 8.88
The NTRU problem with multiple keys arises when a user generates multiple distinct NTRU public keys h_i = g_i/f q by keeping its private key f fixed, and an adversary tries to recover the user’s private key f by collecting multiple instances of public keys h_i . At DCC 2023, Kim et al. introduced a polynomial-time algorithm to address this problem. Subsequently, at ICICS 2024, Song et al. identified a weakness in Kim et al.’s approach and proposed their own method. There are various versions of the NTRU algorithm, resulting in different ways of selecting the parameter f . For instance, in the NIST PQC standardization process, the NTRUEncrypt in Round 1 and NTRU-HPS in Round 3, chooses the private key f in the form f = 1 p to improve efficiency. However, previous studies focus on the scenario where the private key f is a ternary polynomial with a fixed Hamming weight. In this paper, we propose a polynomial time attack against NTRU with multiple keys, assuming that f=1+p*F , where F is a ternary polynomial of degree at most N-1 with a fixed Hamming weight and p=3 . Given the fixed Hamming weight of g_i , we can derive the initial modular equations from different h_i . By employing linearization techniques and exploiting the relationships between the coefficients of the equations, we can establish a system of linear modular equations with ⌊N/2⌋ variables that possesses a unique solution. Using this solution, we can effectively recover the private key f . We conducted experiments using the parameters of NTRU scheme in NIST PQC Competition and achieved successful results with an overwhelming probability. As a by-product, we can naturally extend the multi-key attack scenario to the NTRU-based proxy re-encryption scheme NTRUReEncrypt proposed by Nu ñ ez et al. at AsiaCCS 2015, and successfully recover the user’s private key.
Communication between satellites and mission control centers is currently protected via the Space Data Link Security (SDLS) Protocol. This protocol uses exclusively symmetric cryptography, which makes it resilient against quantum computers, but prevents key updates from achieving post-compromise security and limits operational efficiency, especially in future federated environments. To resolve these issues we designed a key-update/establishment protocol based on PQNoise that leverages KEMs to achieve confidentiality and authenticity. We prove the resulting scheme secure in a slightly modified version of the Bellare–Rogaway-model. To keep the SDLS protocol untouched, the resulting protocol is not used as the handshake phase of a larger data-transmission protocol, but actually run independently, permitting to start from shared keys.
Card-based cryptography performs a secure computation using a deck of playing cards through a series of physical actions, such as shuffling a sequence of cards. In 1989, the first card-based protocol called the five-card trick was proposed to compute the two-input AND function. The five-card trick needs a practical shuffling action called a random cut only once, which shifts a sequence of cards by a random offset. Subsequent research aimed to extend the five-card trick to compute any Boolean function and to reduce the number of cards required to compute it, but Mizuki, Kumamoto, and Sone in 2012 showed that the five-card trick itself can be done with four cards. This Mizuki–Kumamoto–Sone protocol uses the minimal number of cards required for computing two-input Boolean functions (as long as we encode an input bit with two cards); however, it needs a practical step of shuffling action twice, and the question of minimizing the number of steps, particularly the number of shuffling, remains an open problem. In this study, we negatively answer this problem; we prove that any four-card AND protocol cannot be realized using only a single practical shuffle. This implies that the Mizuki–Kumamoto–Sone protocol utilizes the minimal number of practical shuffles. For this, we enumerate all possible practical shuffles and prove that applying any one of them only once either cannot compute the AND function or leak information about the input.
