mirror of
https://github.com/Shiva108/ai-llm-red-team-handbook.git
synced 2026-07-12 15:26:32 +02:00
vc
This commit is contained in:
shiva108
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#!/usr/bin/env python3
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from __future__ import annotations
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import re
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import shutil
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import subprocess
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import textwrap
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import unicodedata
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from pathlib import Path
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ROOT = Path(__file__).resolve().parent.parent
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DOCS = ROOT / "docs"
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BUILD = ROOT / "build" / "handbook_pdf"
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CHAPTERS_DIR = BUILD / "chapters"
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OUTPUT_PDF = ROOT / "AI_LLM_Red_Team_Handbook.pdf"
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OUTPUT_TEX = BUILD / "handbook.tex"
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HEADER_TEX = BUILD / "book-header.tex"
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FRONTMATTER_MD = BUILD / "00_frontmatter.md"
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CHAPTER_FILES = [
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"Chapter_01_Introduction_to_AI_Red_Teaming.md",
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"Chapter_02_Ethics_Legal_and_Stakeholder_Communication.md",
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"Chapter_03_The_Red_Teamers_Mindset.md",
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"Chapter_04_SOW_Rules_of_Engagement_and_Client_Onboarding.md",
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"Chapter_05_Threat_Modeling_and_Risk_Analysis.md",
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"Chapter_06_Scoping_an_Engagement.md",
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"Chapter_07_Lab_Setup_and_Environmental_Safety.md",
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"Chapter_08_Evidence_Documentation_and_Chain_of_Custody.md",
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"Chapter_09_LLM_Architectures_and_System_Components.md",
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"Chapter_10_Tokenization_Context_and_Generation.md",
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"Chapter_11_Plugins_Extensions_and_External_APIs.md",
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"Chapter_12_Retrieval_Augmented_Generation_RAG_Pipelines.md",
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"Chapter_13_Data_Provenance_and_Supply_Chain_Security.md",
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"Chapter_14_Prompt_Injection.md",
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"Chapter_15_Data_Leakage_and_Extraction.md",
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"Chapter_16_Jailbreaks_and_Bypass_Techniques.md",
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"Chapter_17_01_Fundamentals_and_Architecture.md",
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"Chapter_17_02_API_Authentication_and_Authorization.md",
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"Chapter_17_03_Plugin_Vulnerabilities.md",
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"Chapter_17_04_API_Exploitation_and_Function_Calling.md",
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"Chapter_17_05_Third_Party_Risks_and_Testing.md",
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"Chapter_17_06_Case_Studies_and_Defense.md",
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"Chapter_18_Evasion_Obfuscation_and_Adversarial_Inputs.md",
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"Chapter_19_Training_Data_Poisoning.md",
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"Chapter_20_Model_Theft_and_Membership_Inference.md",
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"Chapter_21_Model_DoS_Resource_Exhaustion.md",
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"Chapter_22_Cross_Modal_Multimodal_Attacks.md",
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"Chapter_23_Advanced_Persistence_Chaining.md",
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"Chapter_24_Social_Engineering_LLMs.md",
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"Chapter_25_Advanced_Adversarial_ML.md",
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"Chapter_26_Supply_Chain_Attacks_on_AI.md",
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"Chapter_27_Federated_Learning_Attacks.md",
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"Chapter_28_AI_Privacy_Attacks.md",
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"Chapter_29_Model_Inversion_Attacks.md",
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"Chapter_30_Backdoor_Attacks.md",
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"Chapter_31_AI_System_Reconnaissance.md",
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"Chapter_32_Automated_Attack_Frameworks.md",
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"Chapter_33_Red_Team_Automation.md",
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"Chapter_34_Defense_Evasion_Techniques.md",
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"Chapter_35_Post-Exploitation_in_AI_Systems.md",
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"Chapter_36_Reporting_and_Communication.md",
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"Chapter_37_Remediation_Strategies.md",
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"Chapter_38_Continuous_Red_Teaming.md",
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"Chapter_39_AI_Bug_Bounty_Programs.md",
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"Chapter_40_Compliance_and_Standards.md",
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"Chapter_41_Industry_Best_Practices.md",
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"Chapter_42_Case_Studies_and_War_Stories.md",
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"Chapter_43_Future_of_AI_Red_Teaming.md",
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"Chapter_44_Emerging_Threats.md",
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"Chapter_45_Building_an_AI_Red_Team_Program.md",
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"Chapter_46_Conclusion_and_Next_Steps.md",
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]
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BROKEN_IMAGE_MAP = {
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"docs/assets/rec28_jailbreak_vs_injection_matrix.png": "docs/assets/rec28_jailbreak_vs_injection.png",
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"docs/assets/rec29_alignment_tension_diagram.png": "docs/assets/rec29_alignment_tension.png",
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"docs/assets/rec30_trust_map_diagram.png": "docs/assets/rec30_trust_map.png",
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"docs/assets/rec31_function_injection_diagram.png": "docs/assets/rec31_function_injection.png",
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"docs/assets/rec32_tokenization_gap_diagram.png": "docs/assets/rec32_tokenization_gap.png",
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"docs/assets/rec33_evasion_spectrum_matrix.png": "docs/assets/rec33_evasion_spectrum.png",
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"docs/assets/rec34_gcg_optimization_flow.png": "docs/assets/rec34_gcg_optimization.png",
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"docs/assets/rec35_poisoned_training_flow.png": "docs/assets/rec35_poisoned_training.png",
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"docs/assets/rec36_model_task_superposition.png": "docs/assets/rec36_superposition.png",
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"docs/assets/rec37_backdoor_activation_sequence.png": "docs/assets/rec37_backdoor_activation.png",
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"docs/assets/rec38_supply_chain_poisoning_map.png": "docs/assets/rec38_poisoning_map.png",
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"docs/assets/rec39_model_extraction_flow.png": "docs/assets/rec39_model_extraction.png",
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"docs/assets/rec40_mia_architecture_diagram.png": "docs/assets/rec40_mia_architecture.png",
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}
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MERMAID_REPLACEMENTS = {
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("Chapter_07_Lab_Setup_and_Environmental_Safety.md", 0): (
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"{ width=78% }\n"
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),
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("Chapter_18_Evasion_Obfuscation_and_Adversarial_Inputs.md", 0): "",
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("Chapter_42_Case_Studies_and_War_Stories.md", 0): (
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"{ width=78% }\n"
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),
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("Chapter_45_Building_an_AI_Red_Team_Program.md", 0): "",
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("Chapter_45_Building_an_AI_Red_Team_Program.md", 1): "",
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("Chapter_46_Conclusion_and_Next_Steps.md", 0): "",
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("Chapter_46_Conclusion_and_Next_Steps.md", 1): "",
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}
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ADMONITION_LABELS = {
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"NOTE": "Note",
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"TIP": "Tip",
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"IMPORTANT": "Important",
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"WARNING": "Warning",
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"CAUTION": "Caution",
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}
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def ensure_tool(name: str) -> None:
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if shutil.which(name) is None:
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raise SystemExit(f"Missing required tool: {name}")
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def write_text(path: Path, text: str) -> None:
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path.parent.mkdir(parents=True, exist_ok=True)
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path.write_text(text, encoding="utf-8")
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def normalize_asset_paths(text: str) -> str:
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text = text.replace('src="/docs/assets/', 'src="docs/assets/')
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text = text.replace("](/docs/assets/", "](docs/assets/")
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text = text.replace('src="assets/', 'src="docs/assets/')
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text = text.replace("](assets/", "](docs/assets/")
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for broken, fixed in BROKEN_IMAGE_MAP.items():
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text = text.replace(broken, fixed)
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return text
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def normalize_unicode(text: str) -> str:
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text = unicodedata.normalize("NFKC", text)
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replacements = {
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"\ufe0f": "",
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"✅": "[OK]",
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"❌": "[X]",
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"🚨": "Alert:",
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"📝": "Note:",
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"➔": "->",
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"⚠": "[!]",
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"🔴": "[Red]",
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"🔥": "[Fire]",
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"🛡": "[Shield]",
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}
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for old, new in replacements.items():
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text = text.replace(old, new)
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return text
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def strip_local_md_links(text: str) -> str:
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pattern = re.compile(r"\[([^\]]+)\]\((?!https?://)([^)]+\.md(?:#[^)]+)?)\)")
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return pattern.sub(lambda m: m.group(1), text)
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def convert_callouts(text: str) -> str:
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lines = text.splitlines()
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out: list[str] = []
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i = 0
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while i < len(lines):
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line = lines[i]
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m = re.match(r"^>\s*\[!([A-Z]+)\]\s*(.*)$", line)
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if not m:
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out.append(line)
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i += 1
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continue
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label = ADMONITION_LABELS.get(m.group(1), m.group(1).title())
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rest = m.group(2).strip()
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if rest.startswith(">"):
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rest = rest[1:].strip()
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block = [f"> **{label}.**" + (f" {rest}" if rest else "")]
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i += 1
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while i < len(lines) and lines[i].startswith(">"):
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content = lines[i][1:]
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if content.startswith(" "):
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content = content[1:]
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block.append(f"> {content}")
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i += 1
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out.extend(block)
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return "\n".join(out) + "\n"
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def convert_centered_images(text: str) -> str:
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pattern = re.compile(r"<p\s+align=\"center\">\s*(<img\s+[^>]+>)\s*</p>", re.IGNORECASE | re.DOTALL)
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def repl(match: re.Match[str]) -> str:
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tag = match.group(1)
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src_match = re.search(r'src="([^"]+)"', tag, re.IGNORECASE)
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alt_match = re.search(r'alt="([^"]*)"', tag, re.IGNORECASE)
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if not src_match:
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return match.group(0)
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src = src_match.group(1)
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caption = alt_match.group(1).strip() if alt_match else ""
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label = f"" if caption else f""
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return f"{label}{{ width=74% }}\n"
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return pattern.sub(repl, text)
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def replace_mermaid_blocks(filename: str, text: str) -> str:
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lines = text.splitlines(keepends=True)
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out: list[str] = []
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i = 0
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block_index = 0
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while i < len(lines):
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if lines[i].startswith("```mermaid"):
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i += 1
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while i < len(lines) and not lines[i].startswith("```"):
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i += 1
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if i < len(lines):
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i += 1
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replacement = MERMAID_REPLACEMENTS.get((filename, block_index), "")
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if replacement:
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out.append(replacement)
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if not replacement.endswith("\n"):
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out.append("\n")
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block_index += 1
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continue
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out.append(lines[i])
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i += 1
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return "".join(out)
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def cleanup_spacing(text: str) -> str:
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text = re.sub(r"\n{3,}", "\n\n", text)
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return text.strip() + "\n"
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def preprocess_markdown(filename: str, raw_text: str) -> str:
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text = normalize_unicode(raw_text.replace("\r\n", "\n"))
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text = normalize_asset_paths(text)
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text = strip_local_md_links(text)
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text = convert_centered_images(text)
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text = replace_mermaid_blocks(filename, text)
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text = convert_callouts(text)
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text = cleanup_spacing(text)
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return text
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def frontmatter_markdown() -> str:
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return textwrap.dedent(
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r"""
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---
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title-meta: "AI LLM Red Team Handbook"
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author-meta: "Shiva108"
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date-meta: "April 2026"
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lang: "en-US"
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papersize: "a4"
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documentclass: "book"
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classoption:
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- "11pt"
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- "oneside"
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- "openany"
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colorlinks: true
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linkcolor: black
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urlcolor: black
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toc-depth: 2
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secnumdepth: 3
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---
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```{=latex}
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\frontmatter
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\begin{titlepage}
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\thispagestyle{empty}
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\centering
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\vspace*{1.2cm}
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\includegraphics[width=0.94\textwidth]{docs/assets/cover_1920.png}
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\vspace{1.8cm}
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{\Huge\bfseries AI LLM Red Team Handbook\par}
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\vspace{0.5cm}
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{\Large The Complete Consultant's Guide to AI \& LLM Security Testing\par}
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\vspace{1.2cm}
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{\large Shiva108\par}
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\vfill
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{\large April 2026\par}
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\end{titlepage}
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\clearpage
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\thispagestyle{empty}
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\null
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\vfill
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\begin{center}
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{\Large About This Edition\par}
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\end{center}
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\vspace{1em}
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This publication consolidates the full handbook into a single print-style volume.
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It preserves the original chapter order, illustrations, and technical material while
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reformatting the content for continuous reading and offline distribution.
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\vspace{1em}
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\noindent\textbf{Authorized use only.} The techniques documented in this book are intended
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for defensive research, training, and authorized security testing.
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\clearpage
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\pdfbookmark[0]{Contents}{contents}
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\tableofcontents
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\clearpage
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\mainmatter
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```
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||||
"""
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||||
).strip() + "\n"
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||||
def latex_header() -> str:
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return textwrap.dedent(
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r"""
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\usepackage[a4paper,margin=1in,headheight=16pt]{geometry}
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||||
\usepackage{graphicx}
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||||
\usepackage{float}
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||||
\usepackage{booktabs}
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||||
\usepackage{longtable}
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||||
\usepackage{array}
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||||
\usepackage{caption}
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||||
\usepackage{fancyhdr}
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||||
\usepackage{titlesec}
|
||||
\usepackage{etoolbox}
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||||
\usepackage{fvextra}
|
||||
\usepackage{microtype}
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||||
\usepackage{xurl}
|
||||
\usepackage{setspace}
|
||||
\usepackage{fontspec}
|
||||
\setmainfont{TeX Gyre Pagella}
|
||||
\setsansfont{TeX Gyre Heros}
|
||||
\setmonofont{DejaVu Sans Mono}
|
||||
\setstretch{1.08}
|
||||
\setlength{\emergencystretch}{3em}
|
||||
\makeatletter
|
||||
\def\maxwidth{\ifdim\Gin@nat@width>\linewidth\linewidth\else\Gin@nat@width\fi}
|
||||
\def\maxheight{\ifdim\Gin@nat@height>0.82\textheight 0.82\textheight\else\Gin@nat@height\fi}
|
||||
\makeatother
|
||||
\setkeys{Gin}{width=\maxwidth,height=\maxheight,keepaspectratio}
|
||||
\captionsetup{font=small,labelfont=bf}
|
||||
\DefineVerbatimEnvironment{Highlighting}{Verbatim}{breaklines,breakanywhere,commandchars=\\\{\}}
|
||||
\pagestyle{fancy}
|
||||
\fancyhf{}
|
||||
\fancyhead[L]{\nouppercase{\leftmark}}
|
||||
\fancyhead[R]{AI LLM Red Team Handbook}
|
||||
\fancyfoot[C]{\thepage}
|
||||
\renewcommand{\headrulewidth}{0.4pt}
|
||||
\renewcommand{\footrulewidth}{0pt}
|
||||
\titleformat{\chapter}[display]
|
||||
{\normalfont\huge\bfseries}
|
||||
{\chaptertitlename\ \thechapter}
|
||||
{0.5em}
|
||||
{\Huge}
|
||||
\titlespacing*{\chapter}{0pt}{-10pt}{24pt}
|
||||
\pretocmd{\chapter}{\cleardoublepage}{}{}
|
||||
"""
|
||||
).strip() + "\n"
|
||||
|
||||
|
||||
def build_sources() -> list[Path]:
|
||||
if BUILD.exists():
|
||||
shutil.rmtree(BUILD)
|
||||
CHAPTERS_DIR.mkdir(parents=True, exist_ok=True)
|
||||
|
||||
write_text(FRONTMATTER_MD, frontmatter_markdown())
|
||||
write_text(HEADER_TEX, latex_header())
|
||||
|
||||
processed_files = [FRONTMATTER_MD]
|
||||
for index, filename in enumerate(CHAPTER_FILES, start=1):
|
||||
source = DOCS / filename
|
||||
text = preprocess_markdown(filename, source.read_text(encoding="utf-8"))
|
||||
output = CHAPTERS_DIR / f"{index:02d}_{filename}"
|
||||
write_text(output, text)
|
||||
processed_files.append(output)
|
||||
return processed_files
|
||||
|
||||
|
||||
def run(cmd: list[str], cwd: Path) -> None:
|
||||
subprocess.run(cmd, cwd=cwd, check=True)
|
||||
|
||||
|
||||
def run_latex(cmd: list[str], cwd: Path, expected_pdf: Path) -> None:
|
||||
result = subprocess.run(cmd, cwd=cwd, check=False)
|
||||
if result.returncode != 0 and not expected_pdf.exists():
|
||||
raise SystemExit(f"LaTeX build failed: {' '.join(cmd)}")
|
||||
|
||||
|
||||
def build_pdf() -> None:
|
||||
ensure_tool("pandoc")
|
||||
ensure_tool("xelatex")
|
||||
sources = build_sources()
|
||||
|
||||
pandoc_cmd = [
|
||||
"pandoc",
|
||||
"--from=markdown+raw_html+smart+pipe_tables+task_lists+link_attributes+tex_math_dollars",
|
||||
"--standalone",
|
||||
"--top-level-division=chapter",
|
||||
"--highlight-style=tango",
|
||||
"--include-in-header",
|
||||
str(HEADER_TEX),
|
||||
"-o",
|
||||
str(OUTPUT_TEX),
|
||||
] + [str(path) for path in sources]
|
||||
run(pandoc_cmd, ROOT)
|
||||
|
||||
expected_pdf = OUTPUT_TEX.with_suffix(".pdf")
|
||||
for _ in range(2):
|
||||
run_latex(
|
||||
[
|
||||
"xelatex",
|
||||
"-interaction=nonstopmode",
|
||||
f"-output-directory={BUILD}",
|
||||
str(OUTPUT_TEX),
|
||||
],
|
||||
ROOT,
|
||||
expected_pdf,
|
||||
)
|
||||
|
||||
generated_pdf = expected_pdf
|
||||
if generated_pdf.exists():
|
||||
shutil.copy2(generated_pdf, OUTPUT_PDF)
|
||||
else:
|
||||
raise SystemExit("Expected PDF was not generated.")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
build_pdf()
|
||||
Reference in New Issue
Block a user