CVE-2026-62675

Omnigent is an open-source AI agent framework and meta-harness for orchestrating coding agents. Prior to 0.3.0, multipart POST /v1/sessions accepts an authenticated user's agent bundle and omnigent/server/bundles.py validate_agent_bundle does not reject a tools..callable dotted Python path. omnigent/runner/tool_dispatch.py _resolve_spec_callable imports the specified module and _execute_spec_callable_tool invokes the resolved function, allowing a bundle to select subprocess.check_output and execute a local command with the runner process permissions. This can expose runner files, environment variables, credentials, workspace data, internal services, and availability without administrator access. This issue is fixed in version 0.3.0.

Omnigent is an open-source AI agent framework and meta-harness for orchestrating coding agents. Prior to 0.3.0, multipart POST /v1/sessions accepts an authenticated user's agent bundle and omnigent/server/bundles.py validate_agent_bundle does not reject a tools..callable dotted Python path. omnigent/runner/tool_dispatch.py _resolve_spec_callable imports the specified module and _execute_spec_callable_tool invokes the resolved function, allowing a bundle to select subprocess.check_output and execute a local command with the runner process permissions. This can expose runner files, environment variables, credentials, workspace data, internal services, and availability without administrator access. This issue is fixed in version 0.3.0.

Summary

An authenticated user can upload a crafted agent bundle that defines a server-side Python callable tool. The server validates the uploaded bundle, but it does not block dangerous callable: paths in untrusted user-provided agent configs.

When the tool is invoked, the runner imports and executes that Python callable. A crafted bundle can point the tool at subprocess.check_output, which lets the attacker run a local command on the runner machine.

This is serious because hosted Omnigent deployments can have multiple users and shared or managed runner hosts. A normal logged-in user should not be able to make the runner execute arbitrary local commands.

Details

The uploaded bundle path is reachable through session creation. Omnigent supports custom agent bundles through multipart POST /v1/sessions; the Web UI uses this same endpoint for custom agents:

Create custom agent builds and uploads a bundle
createBundledSession posts the bundle to /v1/sessions

A crafted bundle can also be submitted directly through the API/CLI when creating a session from agent YAML. The PoC below uses this direct bundle shape so the vulnerable trust boundary is easy to reproduce.

On the server, uploaded bundles are validated here: validate_agent_bundle

The validator already treats uploaded bundles as untrusted in some ways. For example, it disables server-side environment expansion and can enforce a policy-handler allowlist:

spec = load(
    bundle_bytes,
    dest=Path(tmpdir) / "agent",
    expand_env=False,
    enforce_handler_allowlist=enforce_handler_allowlist,
)

However, the same validation does not reject tools.<name>.callable entries in an uploaded agent bundle. Python callable tools are an intended trusted/operator feature, but the upload path accepts them from tenant-provided bundles too.

The docs describe server-side Python callable tools here: Python function tool docs
Later, the runner resolves and executes those callables: _resolve_spec_callable imports the dotted path

mod = importlib.import_module(module_name)
fn = getattr(mod, attr_name, None)

_execute_spec_callable_tool calls the resolved function

result = await asyncio.to_thread(resolved, **args)

The high-level tool dispatcher falls back to this callable execution path: execute_tool callable fallback

output = await _execute_spec_callable_tool(tool_name, args, agent_spec=agent_spec)

The problem is the trust boundary. Python callables are a trusted local developer feature, but uploaded agent bundles can be user-controlled in a hosted/multi-user server. The upload validator blocks some trusted-only policy behavior, but it does not block trusted-only tool callables.

Suggested fix: when validating HTTP-uploaded bundles on a shared/multi-user server, reject server-side Python callable tools unless they are explicitly allowlisted by the operator. A conservative fix would reject callable: tool paths for tenant-uploaded bundles, while keeping trusted local/operator-authored configs working. …

Omnigent is an open-source AI agent framework and meta-harness for orchestrating coding agents. Prior to 0.3.0, multipart POST /v1/sessions accepts an authenticated user's agent bundle and omnigent/server/bundles.py validate_agent_bundle does not reject a tools..callable dotted Python path. omnigent/runner/tool_dispatch.py _resolve_spec_callable imports the specified module and _execute_spec_callable_tool invokes the resolved function, allowing a bundle to select subprocess.check_output and execute a local command with the runner process permissions. This can expose runner files, environment variables, credentials, workspace data, internal services, and availability without administrator access. This issue is fixed in version 0.3.0.

Omnigent is an open-source AI agent framework and meta-harness for orchestrating coding agents. Prior to 0.3.0, multipart POST /v1/sessions accepts an authenticated user's agent bundle and omnigent/server/bundles.py validate_agent_bundle does not reject a tools..callable dotted Python path. omnigent/runner/tool_dispatch.py _resolve_spec_callable imports the specified module and _execute_spec_callable_tool invokes the resolved function, allowing a bundle to select subprocess.check_output and execute a local command with the runner process permissions. This can expose runner files, environment variables, credentials, workspace data, internal services, and availability without administrator access. This issue is fixed in version 0.3.0.

Summary

An authenticated user can upload a crafted agent bundle that defines a server-side Python callable tool. The server validates the uploaded bundle, but it does not block dangerous callable: paths in untrusted user-provided agent configs.

When the tool is invoked, the runner imports and executes that Python callable. A crafted bundle can point the tool at subprocess.check_output, which lets the attacker run a local command on the runner machine.

This is serious because hosted Omnigent deployments can have multiple users and shared or managed runner hosts. A normal logged-in user should not be able to make the runner execute arbitrary local commands.

Details

The uploaded bundle path is reachable through session creation. Omnigent supports custom agent bundles through multipart POST /v1/sessions; the Web UI uses this same endpoint for custom agents:

Create custom agent builds and uploads a bundle
createBundledSession posts the bundle to /v1/sessions

A crafted bundle can also be submitted directly through the API/CLI when creating a session from agent YAML. The PoC below uses this direct bundle shape so the vulnerable trust boundary is easy to reproduce.

On the server, uploaded bundles are validated here: validate_agent_bundle

The validator already treats uploaded bundles as untrusted in some ways. For example, it disables server-side environment expansion and can enforce a policy-handler allowlist:

spec = load(
    bundle_bytes,
    dest=Path(tmpdir) / "agent",
    expand_env=False,
    enforce_handler_allowlist=enforce_handler_allowlist,
)

However, the same validation does not reject tools.<name>.callable entries in an uploaded agent bundle. Python callable tools are an intended trusted/operator feature, but the upload path accepts them from tenant-provided bundles too.

The docs describe server-side Python callable tools here: Python function tool docs
Later, the runner resolves and executes those callables: _resolve_spec_callable imports the dotted path

mod = importlib.import_module(module_name)
fn = getattr(mod, attr_name, None)

_execute_spec_callable_tool calls the resolved function

result = await asyncio.to_thread(resolved, **args)

The high-level tool dispatcher falls back to this callable execution path: execute_tool callable fallback

output = await _execute_spec_callable_tool(tool_name, args, agent_spec=agent_spec)

The problem is the trust boundary. Python callables are a trusted local developer feature, but uploaded agent bundles can be user-controlled in a hosted/multi-user server. The upload validator blocks some trusted-only policy behavior, but it does not block trusted-only tool callables.

Suggested fix: when validating HTTP-uploaded bundles on a shared/multi-user server, reject server-side Python callable tools unless they are explicitly allowlisted by the operator. A conservative fix would reject callable: tool paths for tenant-uploaded bundles, while keeping trusted local/operator-authored configs working. …

Summary

An authenticated user can upload a crafted agent bundle that defines a server-side Python callable tool. The server validates the uploaded bundle, but it does not block dangerous callable: paths in untrusted user-provided agent configs.

When the tool is invoked, the runner imports and executes that Python callable. A crafted bundle can point the tool at subprocess.check_output, which lets the attacker run a local command on the runner machine.

This is serious because hosted Omnigent deployments can have multiple users and shared or managed runner hosts. A normal logged-in user should not be able to make the runner execute arbitrary local commands.

Details

The uploaded bundle path is reachable through session creation. Omnigent supports custom agent bundles through multipart POST /v1/sessions; the Web UI uses this same endpoint for custom agents:

Create custom agent builds and uploads a bundle
createBundledSession posts the bundle to /v1/sessions

A crafted bundle can also be submitted directly through the API/CLI when creating a session from agent YAML. The PoC below uses this direct bundle shape so the vulnerable trust boundary is easy to reproduce.

On the server, uploaded bundles are validated here: validate_agent_bundle

The validator already treats uploaded bundles as untrusted in some ways. For example, it disables server-side environment expansion and can enforce a policy-handler allowlist:

spec = load(
    bundle_bytes,
    dest=Path(tmpdir) / "agent",
    expand_env=False,
    enforce_handler_allowlist=enforce_handler_allowlist,
)

However, the same validation does not reject tools.<name>.callable entries in an uploaded agent bundle. Python callable tools are an intended trusted/operator feature, but the upload path accepts them from tenant-provided bundles too.

The docs describe server-side Python callable tools here: Python function tool docs
Later, the runner resolves and executes those callables: _resolve_spec_callable imports the dotted path

mod = importlib.import_module(module_name)
fn = getattr(mod, attr_name, None)

_execute_spec_callable_tool calls the resolved function

result = await asyncio.to_thread(resolved, **args)

The high-level tool dispatcher falls back to this callable execution path: execute_tool callable fallback

output = await _execute_spec_callable_tool(tool_name, args, agent_spec=agent_spec)

The problem is the trust boundary. Python callables are a trusted local developer feature, but uploaded agent bundles can be user-controlled in a hosted/multi-user server. The upload validator blocks some trusted-only policy behavior, but it does not block trusted-only tool callables.

Suggested fix: when validating HTTP-uploaded bundles on a shared/multi-user server, reject server-side Python callable tools unless they are explicitly allowlisted by the operator. A conservative fix would reject callable: tool paths for tenant-uploaded bundles, while keeping trusted local/operator-authored configs working. …