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layout default
title Chapter 6: Offensive Security Mode and Specialized Workloads
nav_order 6
parent SWE-agent Tutorial

Chapter 6: Offensive Security Mode and Specialized Workloads

Welcome to Chapter 6: Offensive Security Mode and Specialized Workloads. In this part of SWE-agent Tutorial: Autonomous Repository Repair and Benchmark-Driven Engineering, you will build an intuitive mental model first, then move into concrete implementation details and practical production tradeoffs.

This chapter explains workload specialization and when to use security-focused variants.

Learning Goals

  • understand EnIGMA mode scope and constraints
  • decide when specialized versions are appropriate
  • isolate high-risk workflows operationally
  • align capabilities with governance requirements

Scope Notes

SWE-agent's EnIGMA path targets offensive cybersecurity challenge workflows. Keep these environments isolated and policy-governed, and follow project guidance on version alignment.

Source References

Summary

You now understand how specialized security workloads fit into the broader SWE-agent ecosystem.

Next: Chapter 7: Development and Contribution Workflow

Depth Expansion Playbook

Source Code Walkthrough

sweagent/agent/models.py

The ReplayModelConfig class in sweagent/agent/models.py handles a key part of this chapter's functionality:

class ReplayModelConfig(GenericAPIModelConfig):
    replay_path: Path = Field(description="Path to replay file when using the replay model.")

    per_instance_cost_limit: float = Field(
        default=0.0, description="Cost limit for every instance (task). This is a dummy value here."
    )
    total_cost_limit: float = Field(
        default=0.0, description="Cost limit for all instances (tasks). This is a dummy value here."
    )

    name: Literal["replay"] = Field(default="replay", description="Model name.")

    model_config = ConfigDict(extra="forbid")


class InstantEmptySubmitModelConfig(GenericAPIModelConfig):
    """Model that immediately submits an empty patch"""

    name: Literal["instant_empty_submit"] = Field(default="instant_empty_submit", description="Model name.")

    per_instance_cost_limit: float = Field(
        default=0.0, description="Cost limit for every instance (task). This is a dummy value here."
    )
    total_cost_limit: float = Field(
        default=0.0, description="Cost limit for all instances (tasks). This is a dummy value here."
    )
    delay: float = 0.0
    """Delay before answering"""

    model_config = ConfigDict(extra="forbid")

This class is important because it defines how SWE-agent Tutorial: Autonomous Repository Repair and Benchmark-Driven Engineering implements the patterns covered in this chapter.

sweagent/agent/models.py

The InstantEmptySubmitModelConfig class in sweagent/agent/models.py handles a key part of this chapter's functionality:

class InstantEmptySubmitModelConfig(GenericAPIModelConfig):
    """Model that immediately submits an empty patch"""

    name: Literal["instant_empty_submit"] = Field(default="instant_empty_submit", description="Model name.")

    per_instance_cost_limit: float = Field(
        default=0.0, description="Cost limit for every instance (task). This is a dummy value here."
    )
    total_cost_limit: float = Field(
        default=0.0, description="Cost limit for all instances (tasks). This is a dummy value here."
    )
    delay: float = 0.0
    """Delay before answering"""

    model_config = ConfigDict(extra="forbid")


class HumanModelConfig(GenericAPIModelConfig):
    name: Literal["human"] = Field(default="human", description="Model name.")

    per_instance_cost_limit: float = Field(
        default=0.0, description="Cost limit for every instance (task). This is a dummy value here."
    )
    total_cost_limit: float = Field(default=0.0, description="Cost limit for all instances (tasks).")
    cost_per_call: float = 0.0
    catch_eof: bool = True
    """Whether to catch EOF and return 'exit' when ^D is pressed. Set to False when used in human_step_in mode."""
    model_config = ConfigDict(extra="forbid")

This class is important because it defines how SWE-agent Tutorial: Autonomous Repository Repair and Benchmark-Driven Engineering implements the patterns covered in this chapter.

sweagent/agent/models.py

The HumanModelConfig class in sweagent/agent/models.py handles a key part of this chapter's functionality:

class HumanModelConfig(GenericAPIModelConfig):
    name: Literal["human"] = Field(default="human", description="Model name.")

    per_instance_cost_limit: float = Field(
        default=0.0, description="Cost limit for every instance (task). This is a dummy value here."
    )
    total_cost_limit: float = Field(default=0.0, description="Cost limit for all instances (tasks).")
    cost_per_call: float = 0.0
    catch_eof: bool = True
    """Whether to catch EOF and return 'exit' when ^D is pressed. Set to False when used in human_step_in mode."""
    model_config = ConfigDict(extra="forbid")


class HumanThoughtModelConfig(HumanModelConfig):
    name: Literal["human_thought"] = Field(default="human_thought", description="Model name.")

    per_instance_cost_limit: float = Field(
        default=0.0, description="Cost limit for every instance (task). This is a dummy value here."
    )
    total_cost_limit: float = Field(
        default=0.0, description="Cost limit for all instances (tasks). This is a dummy value here."
    )
    cost_per_call: float = 0.0

    model_config = ConfigDict(extra="forbid")


ModelConfig = Annotated[
    GenericAPIModelConfig
    | ReplayModelConfig

This class is important because it defines how SWE-agent Tutorial: Autonomous Repository Repair and Benchmark-Driven Engineering implements the patterns covered in this chapter.

sweagent/agent/models.py

The HumanThoughtModelConfig class in sweagent/agent/models.py handles a key part of this chapter's functionality:

class HumanThoughtModelConfig(HumanModelConfig):
    name: Literal["human_thought"] = Field(default="human_thought", description="Model name.")

    per_instance_cost_limit: float = Field(
        default=0.0, description="Cost limit for every instance (task). This is a dummy value here."
    )
    total_cost_limit: float = Field(
        default=0.0, description="Cost limit for all instances (tasks). This is a dummy value here."
    )
    cost_per_call: float = 0.0

    model_config = ConfigDict(extra="forbid")


ModelConfig = Annotated[
    GenericAPIModelConfig
    | ReplayModelConfig
    | InstantEmptySubmitModelConfig
    | HumanModelConfig
    | HumanThoughtModelConfig,
    Field(union_mode="left_to_right"),
]


class GlobalStats(PydanticBaseModel):
    """This class tracks usage numbers (costs etc.) across all instances."""

    total_cost: float = 0
    """Cumulative cost for all instances so far"""

This class is important because it defines how SWE-agent Tutorial: Autonomous Repository Repair and Benchmark-Driven Engineering implements the patterns covered in this chapter.

How These Components Connect

flowchart TD
    A[ReplayModelConfig]
    B[InstantEmptySubmitModelConfig]
    C[HumanModelConfig]
    D[HumanThoughtModelConfig]
    E[GlobalStats]
    A --> B
    B --> C
    C --> D
    D --> E
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