TL; DR. The actual problems with LLMs stem from their design structure rather than their input strings. The research shows that pipelines leak trust at every stage from text normalization to decoding and planning and memory and tools and caches which allow interpretations to become permissions. The measurement process depends on experiments based on mechanisms and non-operational metrics. The solutions operate at interface points instead of keyword filters because they implement provenance tracking and context sealing and plan re-validation at tool boundaries and memory and planner interfaces.

1) Core Claim

Modern systems operate through multiple models which replace the need for a single unified model. They are pipelines. The system produces operational instructions through intermediate products which also deliver analytical data. The main system failure occurs because of unverified trust inheritance. The pre-stage produces authorized text that all following processing components recognize as valid. The system now functions according to “what the system is allowed to do” instead of “what the model thinks you meant.”

2) What Is Distinctive Here

Taxonomies organize attacks based on their jailbreak methods together with their prompt types. This work groups by enabling mechanisms. Different surface prompts face the same internal obstacles which stop them from achieving their complete potential. The mapping process allows you to conduct coverage audits which reveal the defense mechanisms your security controls protect and the ones that stay unguarded.

3) Measurement in One Paragraph

Black-box tests against commercial chat APIs. Each trial needs to start with a completely new session. There was no tool calls and no execution. The system bases its output assessments on non-operational metrics through text-based escalation signals which fail to demonstrate actual real-world results. The objective is to determine when and where a pipeline establishes authority through interpretation.

4) Non-Operational Metrics

• DS - Decode Success. The process of extracting original meaning from content that has become distorted or altered.
• IEO - Interpretation Escalation Output. Transition from analysis to implementation-shaped plans or code skeletons.
• POB - Policy-Override Behavior. The self-authorization appears to happen only in particular experimental or exceptional situations.
• PDI - Policy Deviation or Inconsistency without an explicit plan.
• RR - Refusal or Redirect with correct task classification.

The framework generates a minimal vector for regression testing and defense iteration which operates without executing code or tool calls.

5) Three Mechanisms that Recur

• Unvalidated Trust Inheritance. The text output from OCR, parsers, decoders and “intent extractors” gets treated as policy-approved by subsequent processing components. The lack of provenance information and unverified checks between analysis and action stages makes the transition from analysis to action possible.
• Interpretation-to-Action Escalation. The model creates a plan based on hidden signals in the input data and develops implementation frameworks that operate independently of explicit imperative commands. The system demonstrates this pattern through its reward system which provides benefits for helpfulness during all stages except the final one.
• State and Memory Effects. System activation experiences delays because session rules function with cached data and expanded contextual information. The content will reappear in new frames that seem more secure. Your context window operates as a semantic shell which functions beyond being an inactive buffer.

6) Representative Findings

• Transform carriers. The Base64 decoding process happens because the system operates with a helpful design. The decoded content contains more authority than what the user entered in their raw string. Defense implication: All transformed outputs need to be treated as untrusted input before they can be re-classified for use.
• Form-induced misclassification. The text maintains its fundamental meaning through the use of meter and rhyme and other stylistic elements which help reduce policy triggers. The system generates output text in the form of a plan. Defense implication: classify semantics, not form.
• Normalization gaps. Users employ Leetspeak and typos to evade security filters by using semantic manipulation techniques. The defense mechanism requires running normalization and semantic distance gates as a first step before policy checks to ensure policy enforcement on the normalized form.

The wider taxonomy includes 7 mechanism classes which cover obfuscation and modality bridges and structural steering and statefulness and ecosystem boundaries and social and self-reflexive steering and agent risks.

7) Capability-Scaling vs Safety-Scaling

The research shows that better decoding and inference abilities lead to increased IEO rates when guardrails do not match at the same level of interpretation. This is not a constant of nature. Real-world systems follow a standard pattern when interpretation grows without architectural controls which leads to deteriorating system problems.

8) Architectural Principles

The system needs to treat decoder and pre-processor outputs identically to how it handles user input. The system requires re-classification operations to take place before any privileged access becomes possible.

• Provenance and Context Sealing. Each section starts with its own unique starting point which serves a specific operational function. The system maintains protection of sensitive instructions from unauthorized changes by untrusted code segments. No silent privilege escalation in the context window.
• Plan Re-validation at gates. The validators should be placed before the planner and tools and memory. A plan needs to lose its status or be removed from use when its authority exceeds what the available evidence demonstrates.

Cache attribution. The reuse of content does not affect its untrusted status. Caches require documentation of their origin.

Track DS, IEO, POB, PDI, RR on every red-team corpus. The regression analysis operates at the interface level instead of the token level.

The defense-in-depth blueprint consists of three main concepts which are referred to as Context Sealing + Provenance + Plan Gates.

9) Why This Matters

• Security mindset. The exploit is the upgrade from meaning to permission. Strings are symptoms. Interfaces are causes.
• Agents and tools. Every tool call produces fresh trust edges. The removal of plan gates would result in Chain-of-Thought transforming into Chain-of-Authority.
• Alignment vs architecture. The localized implementation of niceness through RLHF becomes ineffective because unverified context information and unidentified sources of data cause the solution to spread throughout the entire system.
• Interpretability as control point. The right question is not why a sentence was said, but when a hypothesis became a plan with implied rights.

10) Limits

• Time-bound and configuration-bound to provider defaults and text-only conditions.
• No execution and no tools. The research aims to detect escalation signals instead of assessing their resulting effects.
• Agent stacks require actual implementation of conceptual mechanism classes before they become functional. The replication pack includes sanitized prompts which are accompanied by metric rules and scoring instructions.