Chained Exploits: Advanced Hacking Attacks from Start to Finish
Bibliographic record
Abstract
The complete guide to todays hard-to-defend chained attacks: performing them and preventing them Nowadays, its rare for malicious hackers to rely on just one exploit or tool; instead, they use chained exploits that integrate multiple forms of attack to achieve their goals. Chained exploits are far more complex and far more difficult to defend. Few security or hacking books cover them well and most dont cover them at all. Now theres a book that brings together start-to-finish information about todays most widespread chained exploitsboth how to perform them and how to prevent them. Chained Exploits demonstrates this advanced hacking attack technique through detailed examples that reflect real-world attack strategies, use todays most common attack tools, and focus on actual high-value targets, including credit card and healthcare data. Relentlessly thorough and realistic, this book covers the full spectrum of attack avenues, from wireless networks to physical access and social engineering. Writing for security, network, and other IT professionals, the authors take you through each attack, one step at a time, and then introduce todays most effective countermeasures both technical and human. Coverage includes: Constructing convincing new phishing attacks Discovering which sites other Web users are visiting Wreaking havoc on IT security via wireless networks Disrupting competitors Web sites Performingand preventingcorporate espionage Destroying secure files Gaining access to private healthcare records Attacking the viewers of social networking pages Creating entirely new exploits and more Andrew Whitaker, Director of Enterprise InfoSec and Networking for Training Camp, has been featured in The Wall Street Journal and BusinessWeek. He coauthored Penetration Testing and Network Defense. Andrew was a winner of EC Councils Instructor of Excellence Award. Keatron Evans is President and Chief Security Consultant of Blink Digital Security, LLC, a trainer for Training Camp, and winner of EC Councils Instructor of Excellence Award. Jack B. Voth specializes in penetration testing, vulnerability assessment, and perimeter security. He co-owns The Client Server, Inc., and teaches for Training Camp throughout the United States and abroad. informit.com/aw Cover photograph Corbis / Jupiter Images $49.99 US $59.99 CANADA
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.008 | 0.012 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.029 | 0.020 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".