Daniel Baier , Alexander Basse , Jan-Niclas Hilgert , Martin Lambertz
{"title":"记忆中的 TLS 密钥材料识别和提取:现状与未来挑战","authors":"Daniel Baier , Alexander Basse , Jan-Niclas Hilgert , Martin Lambertz","doi":"10.1016/j.fsidi.2024.301766","DOIUrl":null,"url":null,"abstract":"<div><p>Memory forensics is a crucial part of digital forensics as it can be used to extract valuable information such as running processes, network connections, and encryption keys from memory. The last is especially important when considering the widely used Transport Layer Security (TLS) protocol used to secure internet communication, thus hampering network traffic analysis. Particularly in the context of cybercrime investigations (such as malware analysis), it is therefore paramount for investigators to decrypt TLS traffic. This can provide vital insights into the methods and strategies employed by attackers. For this purpose, it is first and foremost necessary to identify and extract the corresponding TLS key material in memory.</p><p>In this paper, we systematize and evaluate the current state of techniques, tools, and methodologies for identifying and extracting TLS key material in memory. We consider solutions from academia but also identify innovative and promising approaches used “in the wild” that are not considered by the academic literature. Furthermore, we identify the open research challenges and opportunities for future research in this domain. Our work provides a profound foundation for future research in this crucial area.</p></div>","PeriodicalId":48481,"journal":{"name":"Forensic Science International-Digital Investigation","volume":null,"pages":null},"PeriodicalIF":2.0000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666281724000854/pdfft?md5=a76adc8897d71246d0088ed7c98c0315&pid=1-s2.0-S2666281724000854-main.pdf","citationCount":"0","resultStr":"{\"title\":\"TLS key material identification and extraction in memory: Current state and future challenges\",\"authors\":\"Daniel Baier , Alexander Basse , Jan-Niclas Hilgert , Martin Lambertz\",\"doi\":\"10.1016/j.fsidi.2024.301766\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Memory forensics is a crucial part of digital forensics as it can be used to extract valuable information such as running processes, network connections, and encryption keys from memory. The last is especially important when considering the widely used Transport Layer Security (TLS) protocol used to secure internet communication, thus hampering network traffic analysis. Particularly in the context of cybercrime investigations (such as malware analysis), it is therefore paramount for investigators to decrypt TLS traffic. This can provide vital insights into the methods and strategies employed by attackers. For this purpose, it is first and foremost necessary to identify and extract the corresponding TLS key material in memory.</p><p>In this paper, we systematize and evaluate the current state of techniques, tools, and methodologies for identifying and extracting TLS key material in memory. We consider solutions from academia but also identify innovative and promising approaches used “in the wild” that are not considered by the academic literature. Furthermore, we identify the open research challenges and opportunities for future research in this domain. Our work provides a profound foundation for future research in this crucial area.</p></div>\",\"PeriodicalId\":48481,\"journal\":{\"name\":\"Forensic Science International-Digital Investigation\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2024-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2666281724000854/pdfft?md5=a76adc8897d71246d0088ed7c98c0315&pid=1-s2.0-S2666281724000854-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Forensic Science International-Digital Investigation\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2666281724000854\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Forensic Science International-Digital Investigation","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666281724000854","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
TLS key material identification and extraction in memory: Current state and future challenges
Memory forensics is a crucial part of digital forensics as it can be used to extract valuable information such as running processes, network connections, and encryption keys from memory. The last is especially important when considering the widely used Transport Layer Security (TLS) protocol used to secure internet communication, thus hampering network traffic analysis. Particularly in the context of cybercrime investigations (such as malware analysis), it is therefore paramount for investigators to decrypt TLS traffic. This can provide vital insights into the methods and strategies employed by attackers. For this purpose, it is first and foremost necessary to identify and extract the corresponding TLS key material in memory.
In this paper, we systematize and evaluate the current state of techniques, tools, and methodologies for identifying and extracting TLS key material in memory. We consider solutions from academia but also identify innovative and promising approaches used “in the wild” that are not considered by the academic literature. Furthermore, we identify the open research challenges and opportunities for future research in this domain. Our work provides a profound foundation for future research in this crucial area.