npx claudepluginhub vulhunt-re/skills --plugin vulhuntThis skill uses the workspace's default tool permissions.
Perform intra-procedural dataflow analysis to track how data flows within functions.
Analyzes IDA cross-references to find callers, callees, imports, data references, call graphs, and dependency chains using SQL queries on xrefs and imports tables.
Finds function call sites in binaries using VulHunt Lua queries. Useful for analyzing callers of functions, checking call relationships, or identifying API invocations.
Traces user-controlled input from sources like $_GET, req.query to dangerous sinks in PHP, Java, Python, Node.js, .NET apps during whitebox pentesting to assess exploitability.
Share bugs, ideas, or general feedback.
Perform intra-procedural dataflow analysis to track how data flows within functions.
Using the VulHunt MCP tools, open the project (open_project) and run the following Lua query (query_project).
To perform dataflow analysis, use project:calls_matching{}:
local calls = project:calls_matching({
to = <target_call>,
where = function(caller)
return caller:named("<function_name>") and caller:has_call(<target_call>)
end,
using = {
-- Annotate caller parameters
parameters = {var:named "first_param", _},
-- Annotate callees
callees = {
["malloc"] = {inputs = {var:named "size"}},
["strlen"] = {output = var:named "len", inputs = {_}},
["check_len"] = {inputs = {var:sanitised()}}
}
}
})
local results = {}
for _, c in ipairs(calls) do
local entry = {
caller_name = c.caller.name,
call_address = c.call_address,
}
if c.inputs[1] and c.inputs[1].annotation then
entry.arg1_annotation = c.inputs[1].annotation
entry.arg1_source = c.inputs[1].origin.source_address
end
if c.inputs[2] and c.inputs[2].annotation then
entry.arg2_annotation = c.inputs[2].annotation
entry.arg2_source = c.inputs[2].origin.source_address
end
if c.output then
entry.return_annotation = c.output.annotation
end
table.insert(results, entry)
end
return results
Possible values for <target_call>:
"system"AddressValue.new(<hex_addr>) (e.g., <hex_addr> = 0x1234){matching = "<regex>", kind = "symbol"}{matching = "41544155", kind = "bytes"}Inputs and output are of type OperandInfo (see operand-info.md). Origins are of type OperandOrigin (see operand-origin.md).
var:named "x" - Tags a variable with the name "x". This tag follows the data through the function, allowing later checks on where it ends up (e.g., which function argument it flows into)._ - Placeholder for variables that don't need to be tracked.var:sanitised() - Stops taint propagation when a tainted variable flows through that function argument.The annotation set in using appears in c.inputs[N].annotation in the results.
For example, if annotated with var:named "cmd", then c.inputs[1].annotation == "cmd"
indicates the first argument came from that tracked variable.
Example 1: Buffer overflow via memcpy
C code snippet:
void vulnerable_function(int len, char *path) {
char buffer[256];
memcpy(buffer, path, len);
}
Lua query:
local calls = project:calls_matching{
to = "memcpy",
using = {
parameters = {var:named "len", var:named "path"}
}
}
local findings = {}
for _, call in ipairs(calls) do
local len_src = call.inputs[3]
local data_src = call.inputs[2]
if (len_src ~= nil and len_src.annotation == "len") or
(data_src ~= nil and data_src.annotation == "path") then
table.insert(findings, {
caller_address = tostring(call.caller_address),
call_address = tostring(call.call_address),
})
end
end
return findings
Example 2: Command injection via snprintf -> system
C code snippet:
void vulnerable_function(char *cmd) {
char buffer[256];
snprintf(buffer, sizeof(buffer), "sh -c %s", cmd);
system(buffer);
}
Lua query:
local calls = project:calls_matching{
to = "system",
where = function(caller)
return caller:has_call("snprintf")
end,
using = {
callees = {snprintf = {inputs = {var:named "cmd", _, _}}}
}
}
local findings = {}
for _, call in ipairs(calls) do
local src = call.inputs[1]
if src ~= nil and src.annotation == "cmd" then
table.insert(findings, {
caller_address = tostring(call.caller_address),
call_address = tostring(call.call_address),
})
end
end
return findings
Find calls to system() where the argument was built using snprintf():
local calls = project:calls_matching{
to = "system", -- system(cmd)
where = function(caller)
return caller:has_call("snprintf") -- snprintf(cmd, ...)
end,
using = {
callees = {snprintf = {inputs = {var:named "cmd", _, _}}}
}
}
local findings = {}
for _, call in ipairs(calls) do
local src = call.inputs[1]
if src ~= nil and src.annotation == "cmd" then
table.insert(findings, {
snprintf_address = tostring(src.origin.source_address),
caller_name = tostring(call.caller.name),
caller_address = tostring(call.caller_address),
call_address = tostring(call.call_address),
})
end
end
return findings
NOTE: Only change the propagated value if the source changes.
Returns a JSON object containing:
snprintf_address is the address of the call site to snprintfcaller_address is the address of the function that makes the callcall_address is the address of the call site to system (the code block address where the call is made)calls_matchingcalls_matchingURLs to additional documentation pages are available at https://vulhunt.re/llm.txt
/functions) - Use this skill to find target functions by name, address, or pattern before performing dataflow analysis/call-sites) - To find where functions are called without tracking data flow, use this simpler skill instead/decompiler) - View decompiled code to understand function logic before setting up complex dataflow annotations