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utils_sig.py
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utils_sig.py
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#!/usr/bin/python
import angr,claripy
import sys,os
import logging
import copy,re
import networkx
from networkx.algorithms import approximation
import itertools
#logging.basicConfig(level=logging.DEBUG) # adjust to the wanted debug level
dbg_out = True
def test_loader(b,base):
print(b.loader.min_addr)
print(b.loader.max_addr)
print(b.loader.memory[base+0x38])
print(b.arch)
blk = b.factory.block(addr=base+0xc440c4).capstone
for ins in blk.insns:
print(ins)
irsb = b.factory.block(addr=base+0xc440c4).vex
irsb.pp()
for stmt_idx, stmt in enumerate(irsb.statements):
print(stmt_idx)
if hasattr(stmt,'expressions'):
for expr in stmt.expressions:
print(expr.tag)
print(expr)
def load_kernel_image(path,arch,base,segments=None):
load_options = {}
load_options['auto_load_libs'] = False
load_options['main_opts'] = {'backend': 'blob', 'custom_arch': arch, 'custom_base_addr': base, 'segments':segments}
#Use loader.provide_symbol() or loader.provide_symbol_batch() to import symbol table.
#-----------------------------------------------------------------------------------
#def provide_symbol(self, owner, name, offset, size=0, sym_type=None):
# return self.provide_symbol_batch(owner, {name: (offset, size, sym_type)})
#-----------------------------------------------------------------------------------
#Usage: owner --> the Backend object, we can use loader.main_bin
# offset --> the offset relative to 0, not actual kernel load address
# sym_type --> https://github.com/angr/cle/blob/master/cle/backends/__init__.py#L148
b = angr.Project(path, load_options=load_options, arch=arch)
#test_loader(b,base)
return b;
re_reg = 'reg_[\da-f]+_[\d]+_[\d]+'
re_mem = 'mem_[\da-f]+_[\d]+_[\d]+'
re_ret = 'fake_ret_value_[\d]+_[\d]+'
translate_arch = None
#We assume that the reg str looks like "reg_[offset Hex num]_N_[size in bits]"
def translate_reg_name(reg):
#Since this can be called from re.sub(), the parameter is a 'SRE_Match' object, thus we should convert it to string if necessary.
if reg is not str:
reg = reg.group(0)
global translate_arch
if translate_arch == None:
print('translate_reg_name: set the translate_arch at first!')
return reg
if not reg.startswith('reg'):
return reg
tokens = reg.split('_')
if len(tokens) != 4:
return reg
offset = int(tokens[1],base = 16)
size = int(tokens[3])/8
return translate_arch.translate_register_name(offset = offset, size = size) + '_' + tokens[2]
#Replace the reg name in the string with a human-readable form
def make_reg_readable(arch,s):
global translate_arch
translate_arch = arch
return re.sub(re_reg,translate_reg_name,s)
#Given a instruction address, this function will identify which registers/mems are read/write.
#This is done by parsing the generated VEX statements, which should work for all archs.
#Param: addr is the start of a block, size is the block size, if ins_list is provided, only the instructions on the list will be analyzed.
def get_ins_ops_info(proj,addr,size=None,ins_list=None, opt_level=0):
irsb = proj.factory.block(addr,size=size,opt_level=opt_level).vex
#info: addr --> {key:val}
info = {}
index = {}
ss = irsb.statements
for i in range(len(ss)):
if ss[i].tag == 'Ist_IMark':
index[ss[i].addr] = i
ins_list = list(index.keys()) if ins_list is None else [x for x in ins_list if x in index]
#NOTE: this list is arch-dependent
#x30 is link register
#ignore_regs = ['ip','pc','sp','xsp','x30']
ignore_regs = []
#TODO: it seems that VEX doesn't differentiate X0 and W0? But what if this matters?
reg_name = lambda off: proj.arch.translate_register_name(offset=off)
for addr in ins_list:
info[addr] = {}
#Skip the initial IMark
for i in range(index[addr]+1,len(ss)):
stmt = ss[i]
if stmt.tag == 'Ist_Put':
#Reg write
reg = reg_name(stmt.offset)
if not reg in ignore_regs:
info[addr].setdefault('put',set()).add(reg)
#Do some recording heres if it's a 'put_ip' stmt.
#TODO: Add register names if you want to support different archs.
if reg in ('ip','pc'):
e = stmt.expressions
if len(e) == 1 and e[0].tag == 'Iex_Const':
if 'put_ip' in info[addr]:
print('[???]Instruction @ %x has multiple put_ip stmts..' % addr)
info[addr]['put_ip'] = e[0].con.value
elif stmt.tag == 'Ist_Store':
#Mem write
#We only indicate that there is a mem write in this instruction, actual data and addr will be decided in runtime.
info[addr]['store'] = True
elif stmt.tag == 'Ist_Exit':
info[addr]['exit'] = True
elif stmt.tag == 'Ist_IMark':
break
#NOTE: Reg read is special because it's not a statement, but an expression with tag 'Iex_Get'.
#Similarly, mem read is 'Iex_Load' So to capture then, we need to iterate the expressions.
for exp in stmt.expressions:
if exp.tag == 'Iex_Get':
#Reg read
reg = reg_name(exp.offset)
if not reg in ignore_regs:
info[addr].setdefault('get',set()).add(reg)
elif exp.tag == 'Iex_Load':
#Mem read
#Similar to mem write, we only indicate that there is a mem read.
info[addr]['load'] = True
return (info,irsb.jumpkind)
def print_vex_blocks(proj,addrs,opt_level=0):
for addr in addrs:
print('[VEX] ' + hex(addr))
irsb = proj.factory.block(addr,opt_level=opt_level).vex
#irsb.pp()
for stmt_idx, stmt in enumerate(irsb.statements):
print('[' + str(stmt_idx) + '] ' + str(stmt) + ' -- ' + stmt.tag + ' -- ' + type(stmt).__name__)
def get_cfg_acc(proj,start,end):
return proj.analyses.CFGAccurate(context_sensitivity_level=0,starts=[start],call_depth=0,normalize=True)
#Get the CFGFast of the function starting from 'start' and ending at 'end'
def get_cfg_fast(proj,start,end):
# The regions in the image that the CFG should cover
regions = [(start,end)]
# Specify the start addresses of functions need to be analyzed
function_starts = [start]
# It seems that 'regions' and 'start_at_entry' parameters are not supported in this version?
return proj.analyses.CFGFast(symbols=False,regions=regions,start_at_entry=False,function_prologues=False,function_starts=function_starts)
#Get an element from a set
def pick_one(s):
for e in s:
break
return e
#'his' is a sequence of basic block addrs, this function judge whether 'state' has gone through the same history.
def old_days(state,his):
so_far = [x for x in state.history.bbl_addrs]
return str(so_far)[1:-1].startswith(str(his)[1:-1])
#Use DFS to get all the paths from start to target.
#TODO: To deal with paths with loops.
def get_path(cfg,path,target,visited=set()):
n = path[-1]
if n.addr == target.addr:
return path
if n.addr in visited:
return
visited.add(n.addr)
for x in cfg.successors(n):
if x.addr not in visited:
new_path = copy.deepcopy(path)
new_path.append(x)
get_path(cfg,new_path,target,visited)
#The cfg is a DiGraph
def get_all_preds_raw(cfg,n,preds):
preds.add(n)
for x in cfg.predecessors(n):
if x not in preds:
get_all_preds_raw(cfg,x,preds)
#The cfg is a DiGraph
def get_all_preds(cfg,n,preds):
preds.add(n.addr)
for x in cfg.predecessors(n):
if x.addr not in preds:
get_all_preds(cfg,x,preds)
#Given a subgraph instead of a single node, return all predecessors of this subgraph.
def get_all_preds4graph(cfg,g):
preds = set()
en = set([x.addr for x in g.nodes() if g.in_degree(x) == 0])
en = set([get_node_by_addr(cfg,x) for x in en])
for n in en:
t = set()
get_all_preds(cfg,n,t)
preds = preds.union(t)
return preds
#The cfg is a DiGraph
def get_all_succs(cfg,n,succs):
succs.add(n.addr)
for x in cfg.successors(n):
if x.addr not in succs:
get_all_succs(cfg,x,succs)
#Given a subgraph instead of a single node, return all successors of this subgraph.
def get_all_succs4graph(cfg,g):
succs = set()
en = set([x.addr for x in g.nodes() if g.out_degree(x) == 0])
en = set([get_node_by_addr(cfg,x) for x in en])
for n in en:
t = set()
get_all_succs(cfg,n,t)
succs = succs.union(t)
return succs
#Given a CFGAcc or CFGFast and a function start address, return the function CFG which is a DiGraph.
#'simplify' means whether we should optimize the CFG topology to eliminate all absolute control transfer nodes (eg. b,jmp)
def get_func_cfg(cfg,start,normalize=True,sym_tab=None,proj=None,simplify=False):
func = cfg.functions[start]
if func is None:
print('No function at %x' % start)
return None
if normalize:
func.normalize()
#Different from the 'cfg', func_cfg is a networkx.DiGraph.
g = copy.deepcopy(func.transition_graph)
#Do some extra checks
exception_nodes = [hex(x.addr) for x in g.nodes() if x.size is None]
if len(exception_nodes) > 0:
print('[FUNC_CFG] Plz check following nodes, they may contain un-decodable instructions: ' + str(exception_nodes))
#Issue 0: Sometimes this graph will include size 0 node, which represent functions that are called by current function.
#We don't need them actually.
g.remove_nodes_from([x for x in g.nodes() if x.size == 0 or x.size is None])
#Issue 1: This is a hacking, sometimes a function may call a non-return function in the end (e.g. __stack_chk_fail),
#we must ensure that callee node will not have any successors..
#*But* we need Angr proj and sym_table to enable the detection and correction below.
non_ret_funcs = ('__stack_chk_fail')
non_rets = []
if sym_tab and proj:
for n in g.nodes():
irsb = proj.factory.block(n.addr,size=n.size,opt_level=0).vex
if irsb.jumpkind == 'Ijk_Call':
name = get_exit_func_name(proj,irsb,sym_tab)
if name and name in non_ret_funcs:
non_rets += [n]
if non_rets:
g.remove_edges_from(g.out_edges(non_rets))
#If specified, optimize out absolute jump nodes.
if simplify:
#Note that here 'g' is already a deepcopy of original 'transition_graph' in cfg_acc
#So modify 'g' will not affect original cfg_acc.
simplify_cfg_aarch64(proj,g)
return g
def simplify_cfg_aarch64(proj,g):
if not proj:
return g
def _is_abs_jmp_node(n):
if not n.size or n.size != 4:
return False
succs = g.successors(n)
if succs and len(succs) > 1:
return False
cap = proj.factory.block(n.addr,size=4).capstone
opc = cap.insns[0].insn.mnemonic
if opc in ('b','B','prfm'):
return True
return False
absn = [n for n in g.nodes() if _is_abs_jmp_node(n)]
for n in absn:
preds = g.predecessors(n)
succs = g.successors(n)
g.remove_node(n)
if preds and succs:
for p in preds:
g.add_edge(p,succs[0])
return g
#The cfg is a DiGraph.
def get_node_by_addr(cfg,addr,any_addr=False):
nodes = [ x for x in cfg.nodes() if x.addr==addr and x.size is not None]
if nodes:
return sorted(nodes,key=lambda x:x.size)[0]
if any_addr:
nodes = [ x for x in cfg.nodes() if x.size is not None and x.addr <= addr and addr < x.addr + x.size ]
if nodes:
return sorted(nodes,key=lambda x:x.size)[0]
return None
#Below are some signature-related stuff.
def _calc_next_instruction_addr(proj,addr):
if proj.arch.name == 'AARCH64':
return addr + 4
else:
print('Unsupported arch: ' + proj.arch.name)
return addr + 4
#The main purpose is to set up the initial 'formulas' map for the given node in the signature.
#The main task is to identify the address and involved registers for each root instruction in the node.
#Param: g --> sig graph n --> node
def init_sig_node_formulas(proj,g,n,sym_tab=None):
g.node[n]['formulas'] = {}
formulas = g.node[n]['formulas']
(ins_info,jumpkind) = get_ins_ops_info(proj,n.addr,n.size,list(g.node[n]['root_ins']))
g.node[n]['jumpkind'] = jumpkind
#'x30' is link register for 'bl'
ignore_regs = ['ip','pc','sp','xsp','x30','cc_op','cc_ndep','cc_dep1','cc_dep2']
stack_regs = ['sp','xsp']
for addr in ins_info:
if 'exit' in ins_info[addr]:
#An exit instruction.
#'a-g-k' is a addr-guard-jumpkind tuple list.
formulas[addr] = {'type':'exit','a-g-k':[]}
elif 'put_ip' in ins_info[addr] and ins_info[addr]['put_ip'] != _calc_next_instruction_addr(proj,addr):
#We want to capture a special case here.
#The 'exit' type is from 'Ist_Exit' stmt, which usually indicates a conditional jump, but what about unconditional jump?
#Instructions like 'bl' 'b' usually don't have 'Ist_Exit' stmt, what they do is simply set 'ip' register to target address,
#but other normal instructions will also set 'ip' to the next instruction, so here we use a heuristic: if an instruction
#will set 'ip' to somewhere that is not its next instruction (but itself is not of 'exit' type), then it should be an unconditional jump.
formulas[addr] = {'type':'exit','a-g-k':[]}
#Parse the function name if possible.
if sym_tab is not None:
e = sym_tab.lookup(ins_info[addr]['put_ip'])
if e is not None:
g.node[n]['exit_func_name'] = e[1]
formulas[addr]['func_name'] = e[1]
elif 'store' in ins_info[addr]:
#I want to put a special filter here: for the instructions that store sth to stack variables, I want to exclude them from root instructions.
#Because they are very likely to be retrieved later, that's to say in theory they should have out edges in DFG but unfortunately current DFG
#analysis cannot recognize dependencies related to memory location.
#TODO: may consider to improve the DFG analysis to make it able to deal with simple memory dependencies.
if 'get' in ins_info[addr] and any(reg in ins_info[addr]['get'] for reg in stack_regs):
g.node[n]['root_ins'].remove(addr)
g.graph['root_ins'].remove(addr)
continue
#This is a mem store instruction
#a-d-l: addr-data-length tuple list
formulas[addr] = {'type':'store','a-d-l':[]}
elif 'load' in ins_info[addr]:
#This is a mem load instruction
formulas[addr] = {'type':'load'}
#For mem load instruction we only need to care about the regs that are written.
if 'put' in ins_info[addr]:
for reg in ins_info[addr]['put']:
if reg not in ignore_regs:
formulas[addr][reg] = []
else:
#This instruction has nothing to do with mem, it should be a data transfer between regs.
formulas[addr] = {'type':'other'}
if 'put' in ins_info[addr]:
for reg in ins_info[addr]['put']:
if reg not in ignore_regs:
formulas[addr][reg] = []
return
#A signature is basically an attributed CFG, we use DiGraph to implement this, which support attributes for nodes/edges.
#Params: cfg is a DiGraph with normal BBs as nodes.
def init_signature(proj,cfg,addrs,insns=None,pos=None,negs=None,sym_tab=None):
#print [hex(x) for x in addrs]
nodes = [get_node_by_addr(cfg,x) for x in addrs]
#Get in_degree and out_degree in original CFG.
ind = {}
outd = {}
for n in nodes:
ind[n.addr] = cfg.in_degree(n)
outd[n.addr] = cfg.out_degree(n)
#Get subgraph
og = cfg.subgraph(nodes)
og = copy.deepcopy(og)
sigs = []
#Get the weakly connected subgraphs
for g in networkx.weakly_connected_component_subgraphs(og):
#Get the DFG for these nodes
dfgs = get_dfg(proj,[ x for x in g.nodes() if x.size != 0])
#This holds all root instruction addrs of the whole signature graph.
g.graph['root_ins'] = set()
#Set attributes of the nodes in the subgraph
void_node = []
for n in g.nodes():
#The node is of the type 'angr.knowledge.codenode.BlockNode'
#print '---------------------------'
#print '%x,%x' % (n.addr,n.size)
if n.size == 0:
#This should be the start of another function which is called in current function.
#TODO: what information to add here? Maybe the function name?
continue
#The DFG is on the VEx statements (opt_level=0) level
#TODO: do we really need to store DFG for each node?
if n.addr not in dfgs or dfgs[n.addr] is None:
print('No DFG generated for (%x,%x)' % (n.addr,n.size))
g.node[n]['dfg'] = None
#This node should contain only one control-transfer instruction.
root_ins = set([n.addr])
else:
g.node[n]['dfg'] = dfgs[n.addr]
#Identify the root instructions for each node according to its DFG.
root_ins_d = get_root_ins_addr(dfgs[n.addr])
#We have two filter modes: pos/neg markers based and accurate instruction list based.
#If we have DWARF debug information, we should always use the accurate instruction list based filter, which is simply better.
root_ins = set(root_ins_d.keys())
if insns is not None:
root_ins = set(flt_root_ins_acc(g,n,root_ins_d,_get_in_node_addr(n,insns)))
elif pos is not None or negs is not None:
root_ins = set(flt_root_ins_marker(g,n,root_ins,_get_in_node_addr(n,pos),_get_in_node_addr(n,negs)))
if not root_ins:
void_node.append(n)
continue
g.node[n]['root_ins'] = root_ins
g.graph['root_ins'] = g.graph['root_ins'].union(g.node[n]['root_ins'])
#Original code block
#TODO: should we set opt_level = 0 here?
g.node[n]['block'] = proj.factory.block(n.addr,size=n.size)
#Record the in_degree and out_degree in original CFG
g.node[n]['in_d'] = ind[n.addr]
g.node[n]['out_d'] = outd[n.addr]
#Entry format of the formulas dict: addr --> (reg_name,formula)
init_sig_node_formulas(proj,g,n,sym_tab=sym_tab)
for n in void_node:
if ok_to_remove_node(g,n):
g.remove_node(n)
else:
set_padding_node(g,n)
sigs.append(g)
#If the identified patch areas are not within a same sub-graph, we need to organize them into one.
if len(sigs) > 1:
print('Need to combine scattered instructions.')
sigs = combine_subsigs(cfg,sigs)
return sigs
#Return true if removing node n from g doesn't break its connectivity.
#TODO: Any simpler way to decide this?
def ok_to_remove_node(g,n):
g0 = copy.deepcopy(g)
n0 = get_node_by_addr(g0,n.addr)
g0.remove_node(n0)
return len([x for x in networkx.weakly_connected_component_subgraphs(g0)]) <= 1
def combine_subsigs(cfg,sigs):
if not sigs or len(sigs) <= 1 or not cfg:
return sigs
#addrs of all non-padding nodes
addrs = {}
for g in sigs:
for n in g.nodes():
addrs[n.addr] = g.node[n]
#Start to merge the sub-sigs pair by pair.
sg = sigs[0]
for i in range(1,len(sigs)):
sg = _combine_subsigs(cfg,sg,sigs[i])
#TODO: Do we need to develop some heuristics (eg. give up the combined sig if it contains too many padding nodes.)?
sg = copy.deepcopy(sg)
for n in sg.nodes():
if n.addr in addrs:
sg.node[n] = addrs[n.addr]
else:
set_padding_node(sg,n)
sg.graph['root_ins'] = set()
for g in sigs:
sg.graph['root_ins'] = sg.graph['root_ins'].union(g.graph['root_ins'])
return [sg]
#Given a DiGraph and two separate sub-graphs, merge them together.
def _combine_subsigs(cfg,g0,g1):
if not len(g0) or not len(g1):
return g0 if not len(g1) else g1
o_cfg = cfg
#get_cfg_wo_loops() will return a copy of original graph without modifying it.
cfg = get_cfg_wo_loops(o_cfg)
g0 = get_cfg_wo_loops(g0)
g1 = get_cfg_wo_loops(g1)
a0 = set([x.addr for x in g0.nodes()])
a1 = set([x.addr for x in g1.nodes()])
if a0.intersection(a1):
#No padding nodes are needed.
t = a0.union(a1)
nodes = [get_node_by_addr(o_cfg,x) for x in t]
sg = o_cfg.subgraph(nodes)
gs = [g for g in networkx.weakly_connected_component_subgraphs(sg)]
if len(gs) > 1:
#How can this be possible?
print('!!!!Fail to merge two signatures with common nodes??')
return sorted(gs,key=lambda x:len(x))[-1]
p0 = get_all_preds4graph(cfg,g0)
p1 = get_all_preds4graph(cfg,g1)
s0 = get_all_succs4graph(cfg,g0)
s1 = get_all_succs4graph(cfg,g1)
if p0.intersection(a1):
t = p0.intersection(s1)
gs = cluster_padding_nodes(cfg,t)
t = set([x.addr for x in gs[0].nodes()]) if len(gs) > 0 else set([])
elif p1.intersection(a0):
t = p1.intersection(s0)
gs = cluster_padding_nodes(cfg,t)
t = set([x.addr for x in gs[0].nodes()]) if len(gs) > 0 else set([])
else:
#In this case, consider both common predecessor and successor, choose the smaller resulting signature.
#(1)Predecessor
tp = p0.intersection(p1)
if not tp:
print('!!!Null common predecessors')
print(len(g0))
print(len(g1))
print('g0 ' + hex_array_sorted([n.addr for n in g0.nodes()]))
print('a0 ' + hex_array_sorted(a0))
print('p0 ' + hex_array_sorted(p0))
print('g1 ' + hex_array_sorted([n.addr for n in g1.nodes()]))
print('a1 ' + hex_array_sorted(a1))
print('p1 ' + hex_array_sorted(p1))
gs = cluster_padding_nodes(cfg,tp)
en = set()
for g in gs:
en = en.union(set([x.addr for x in g.nodes() if g.out_degree(x) == 0]))
en = [get_node_by_addr(cfg,x,any_addr=True) for x in en]
#Choose a preceding node that minimize the number of padding nodes.
def _calc_common_pred_path(n):
succs = set()
get_all_succs(cfg,n,succs)
pad0 = succs.intersection(p0)
pad1 = succs.intersection(p1)
return pad0.union(pad1)
en = [(x,_calc_common_pred_path(x)) for x in list(en)]
en = sorted(en,key=lambda x:len(x[1]))
#(2)Successor
ts = s0.intersection(s1)
if ts:
gs = cluster_padding_nodes(cfg,ts)
sn = set()
for g in gs:
sn = sn.union(set([x.addr for x in g.nodes() if g.in_degree(x) == 0]))
sn = [get_node_by_addr(cfg,x,any_addr=True) for x in sn]
#Choose a succeding node that minimize the number of padding nodes.
def _calc_common_succ_path(n):
preds = set()
get_all_succs(cfg,n,preds)
pad0 = preds.intersection(s0)
pad1 = preds.intersection(s1)
return pad0.union(pad1)
sn = [(x,_calc_common_succ_path(x)) for x in list(sn)]
sn = sorted(sn,key=lambda x:len(x[1]))
else:
sn = []
if not sn and not en:
#Something very unusual must happen
print('Fail to combine two sub-CFG, possibly there are unrecognized instructions in the function...')
t = set()
else:
t = en[0][1] if not sn or len(en[0][1]) <= len(sn[0][1]) else sn[0][1]
t = t.union(a0).union(a1)
nodes = [get_node_by_addr(o_cfg,x) for x in t]
sg = o_cfg.subgraph(nodes)
gs = [g for g in networkx.weakly_connected_component_subgraphs(sg)]
if len(gs) > 1:
#This should be impossible...
print('!!!After merging sub-sigs, there are still multiple ones..')
else:
print('------Sig w/ padding nodes: ' + str([hex(x.addr) for x in gs[0].nodes()]))
return gs[0]
def cluster_padding_nodes(cfg,addrs):
nodes = [get_node_by_addr(cfg,x) for x in addrs]
sg = cfg.subgraph(nodes)
gs = [g for g in networkx.weakly_connected_component_subgraphs(sg)]
return sorted(gs,key=lambda x:len(x))
def combine_subsigs_steiner(cfg,sigs):
if not sigs or len(sigs) <= 1 or not cfg:
return sigs
#addrs of all non-padding nodes
addrs = {}
for g in sigs:
for n in g.nodes():
addrs[n.addr] = g.node[n]
#steiner tree problem is in general NP-hard, here we use the approximation algorithm in the networkx package.
u_cfg = cfg.to_undirected()
nodes = [get_node_by_addr(u_cfg,x) for x in addrs]
sg = approximation.steiner_tree(u_cfg,nodes)
c_addrs = [x.addr for x in sg.nodes()]
nodes = [get_node_by_addr(cfg,x) for x in c_addrs]
sg = cfg.subgraph(nodes)
sg = copy.deepcopy(sg)
for n in sg.nodes():
if n.addr in addrs:
sg.node[n] = addrs[n.addr]
else:
set_padding_node(sg,n)
sg.graph['root_ins'] = set()
for g in sigs:
sg.graph['root_ins'] = sg.graph['root_ins'].union(g.graph['root_ins'])
return [sg]
def set_padding_node(cfg,n):
cfg.node[n] = {'padding':1,'root_ins':set()}
#insns_d: a dict of root_ins_addr --> rooted_ins_addr set
#acc_list: accurate instruction list that composes the signature.
def flt_root_ins_acc(g,n,insns_d,acc_list,include_last=False,root_in_acc=False):
#(1)First pick up all root instructions from insns_d which are also within acc_list.
root_ins = set(insns_d.keys())
root_ins = root_ins.intersection(set(acc_list))
#(2)See whether all instructions in acc_list have been rooted by root_ins picked in (1), then add those un-rooted instructions to root_ins if root_in_acc is set.
#Else just add enough root_ins until all instructions in acc_list are rooted.
#Make a special optimization here: if there is no root instruction in acc_list and current node has no successors in the sig graph, then just return null.
#Because in this situation, it's very likely that addr2line has added some unnecessary instructions.
if not root_ins and g.out_degree(n) == 0 and g.number_of_nodes() > 1:
return set()
rooted_ins = set()
for r in root_ins:
rooted_ins = rooted_ins.union(insns_d[r])
remain_ins = set(acc_list) - rooted_ins
if root_in_acc:
root_ins = root_ins.union(remain_ins)
else:
cand_root_ins = set(insns_d.keys()) - root_ins
for c in cand_root_ins:
if not remain_ins:
break
if insns_d[c].intersection(remain_ins):
root_ins.add(c)
remain_ins = remain_ins - insns_d[c]
#Then we have a complementary rule: add the 'exit' instruction as root_ins if necessary.
if include_last:
in_deg = g.in_degree(n)
out_deg = g.out_degree(n)
last = n.addr + n.size - 4
if g.number_of_nodes() <= 1 or out_deg > 0:
root_ins.add(last)
return root_ins
def flt_root_ins_marker(g,n,insns,pos,neg):
_in_node = lambda n,m:m>=n.addr and m<n.addr+n.size
_is_null = lambda x:x is None or not x
_flt_pos = lambda ins,m:[x for x in ins if x>=m]
_flt_neg = lambda ins,m:[x for x in ins if x<=m]
in_deg = g.in_degree(n)
out_deg = g.out_degree(n)
if _is_null(pos):
if _is_null(neg):
#Full node is in the signature, no filtering.
return insns
else:
#First few instructions are of interest.
neg = max(neg)
f_insns = _flt_neg(insns,neg)
if _is_null(f_insns):
#It seems that the marked instructions are not root ones, just return pre-filtering insns.
return insns
else:
#Maybe we still need to include the 'exit' in the end..
if out_deg > 0 or g.number_of_nodes() <= 1:
last = n.addr+n.size-4
return set(f_insns).union(set([last])) if last in insns else f_insns
else:
return f_insns
else:
pos = min(pos)
if _is_null(neg):
#Last few instructions are of interest.
f_insns = _flt_pos(insns,pos)
if _is_null(f_insns):
#This should be impossible
print('!!!No root instructions after pos marker: ' + hex(pos))
return insns
return f_insns
else:
#Hang in the middle.
neg = max(neg)
fp_insns = _flt_pos(insns,pos)
fn_insns = _flt_neg(insns,neg)
fpn_insns = _flt_neg(fp_insns,neg)
if _is_null(fpn_insns):
if out_deg == 0 and g.number_of_nodes() > 1 and not _is_null(fn_insns):
return fn_insns
elif in_deg == 0 and not _is_null(fp_insns):
return fp_insns
else:
return insns
else:
if out_deg == 0 and g.number_of_nodes() > 1:
#No successors
return fpn_insns
else:
#Have successors, consider 'exit' instruction.
last = n.addr+n.size-4
return set(fpn_insns).union(set([last])) if last in insns else fpn_insns
_get_in_node_addr = lambda n,ms:[] if ms is None else [x for x in list(ms) if x>=n.addr and x<n.addr+n.size]
def show_signature(sig):
print('---------------------Signature-----------------------')
print('---------------------Graph Information----------------------')
if 'sig_name' in sig.graph:
print('[Sig Name] ' + sig.graph['sig_name'])
if 'func_name' in sig.graph:
print('[Function Name] ' + sig.graph['func_name'])
if 'options' in sig.graph:
print('[options]')
print(sig.graph['options'])
print('[Root Instructions]')
print([hex(x) for x in sig.graph.get('root_ins',[])])
print('---------------------Node Information----------------------')
for node in sig.nodes():
print('>>>>>[%x,%x]<<<<<' % (node.addr,node.size))
print('succs: ' + str([hex(x.addr) for x in sig.successors(node)]))
print('preds: ' + str([hex(x.addr) for x in sig.predecessors(node)]))
if 'padding' in sig.node[node]:
print('~~PADDING~~')
continue
print('jumpkind: ' + sig.node[node]['jumpkind'])
if 'exit_func_name' in sig.node[node]:
print('func: ' + sig.node[node]['exit_func_name'])
if 'fmt_str' in sig.node[node]:
print('fmt_str: ' + sig.node[node]['fmt_str'])
print('root_ins: ' + str([hex(x) for x in sig.node[node]['root_ins']]))
print('formulas:')
for addr in sig.node[node]['formulas']:
inf = sig.node[node]['formulas'][addr]
print('###[%s] %x' % (inf['type'],addr))
if 'a-d-l' in inf:
adl = inf['a-d-l']
for (a,d,l) in adl:
print('[A] %s [D] %s [L] %s' % _sig_get_str((a,d,l)))
elif 'a-g-k' in inf:
agk = inf['a-g-k']
for (a,g,k) in agk:
print('[A] %s [G] %s [K] %s' % _sig_get_str((a,g,k)))
if 'func_name' in inf:
print('[F] %s' % inf['func_name'])
else:
for k in inf:
if k in ('type') or not isinstance(inf[k],list):
continue
print('[' + k + ']')
for e in inf[k]:
print('%s' % _sig_get_str([e]))
def _sig_get_str(tlist):
def _to_str(t):
if isinstance(t,claripy.ast.Base):
return t.hz_repr()
elif isinstance(t,int) or isinstance(t,int):
return hex(t)
return str(t)
return tuple(map(_to_str,tlist))
hex_array = lambda a:str([hex(x) for x in a])
hex_array_sorted = lambda a:str([hex(x) for x in sorted(a)])
#I want to do some trimmings here, reduce some unnecessary (and possibly harmful when matching) nodes in the signature.
def trim_signature(sig,addrs={},options={}):
if options.get('trim_tail_abs_jmp',False):
_trim_tail_abs_jmp(sig)
if options.get('trim_tail_call_args',False):
_trim_tail_call_args(sig)
if options.get('trim_non_tail_roots',False):
_trim_non_tail_roots(sig)
#trim_non_tail_roots-%d-%d
range_trim = [x for x in list(options) if x.find('trim_non_tail_roots-')>=0]
for k in range_trim:
tks = k.split('-')
(n1,n2) = (int(tks[1]),int(tks[2]))
aset = get_insns_for_lines(addrs,n1,n2)
_trim_non_tail_roots(sig,aset)
#farg-ln0-ln1:Xn,Xm
farg = [x for x in list(options) if x.find('farg-')>=0]
for fa in farg:
tks = fa.split('-')
(n1,n2) = (int(tks[1]),int(tks[2]))
aset = get_insns_for_lines(addrs,n1,n2)
_trim_farg_aarch64(sig,aset,options[fa])
#Return the instruction set for a specific line range.
def get_insns_for_lines(addrs,l0,l1):
aset = set()
for ln in addrs:
if ln >= l0 and ln <= l1:
aset = aset.union(addrs[ln])
return aset
#Within the instruction set, only reserve the ones filling the specified registers.
def _trim_farg_aarch64(sig,aset,ps):
for n in sig.nodes():
if 'padding' in sig.node[n]:
continue
formulas = sig.node[n]['formulas']
for k in list(formulas):
if not k in aset:
continue
if formulas[k]['type'] in ('load','other'):
regs = set([x for x in formulas[k] if x != 'type' and isinstance(formulas[k][x],list)])
if not regs.intersection(ps):
formulas.pop(k)
sig.graph['root_ins'].discard(k)
sig.node[n]['root_ins'].discard(k)
#Only reserve the last instruction as the root instruction for each node.
def _trim_non_tail_roots(sig,aset=set()):
for n in sig.nodes():
if 'padding' in sig.node[n]:
continue
formulas = sig.node[n]['formulas']
kl = sorted(list(formulas))
for k in kl[:-1]:
if k in aset:
formulas.pop(k)
sig.graph['root_ins'].discard(k)
sig.node[n]['root_ins'].discard(k)
#For the tail Ijk_Call node, ignore all the root instructions beside the 'call' instruction itself.
#This is useful when sometimes we want to simply include a call below the patch site into the signature as context, while in the meanwhile
#don't want the args of this call to introduce extra noises with their semantic formulas.
def _trim_tail_call_args(sig):
for n in sig.nodes():
if 'padding' in sig.node[n]:
continue
if sig.out_degree(n) != 0 or sig.node[n]['jumpkind'] != 'Ijk_Call':
continue
formulas = sig.node[n]['formulas']
for k in list(formulas):
if formulas[k]['type'] in ('load','other','store'):
formulas.pop(k)
sig.graph['root_ins'].discard(k)
sig.node[n]['root_ins'].discard(k)
#Eliminate all tail nodes that simply do an absolute jump of Ijk_Boring.
def _trim_tail_abs_jmp(sig):
if sig.number_of_nodes() <= 1:
return
def _pure_abs_jmp(n):
if n.size > 4 or sig.node[n]['out_d'] > 1 or sig.node[n]['jumpkind'] != 'Ijk_Boring':
return False
form = sig.node[n]['formulas'][n.addr]
if form['type'] == 'exit':
for _,g,_ in form['a-g-k']:
if str(g).split(' ')[1][:-1] != 'True':
return False
return True
to_remove = []
for n in sig.nodes():
if 'padding' in sig.node[n]:
continue
if sig.out_degree(n) == 0 and _pure_abs_jmp(n):
to_remove.append(n)
sig.remove_nodes_from(to_remove)
#There can be 'Ijk_Call' nodes in the signature, for these callees, what can we do if we have their function prototype?
#One thing for example is that we can obtain the format string for 'printk', instead of a simple global str pointer loaded into x0. Thus
#we can compare the format string contents to locate patch.
def analyze_func_args_aarch64(image,base,sig,options={}):
if options.get('match_fmt_str',False):
_analyze_fmt_str_aarch64(image,base,sig)
fmt_func_map_aarch64 = {
'printk':'x0',
'snprintf':'x2',
'__dynamic_pr_debug':'x1',
'seq_printf':'x1',
'_dev_info':'x1',
'dev_err':'x1',
'dprintk':'x1',
'write_str':'x1',
}
#If there is any callee in the signature that has a format string as one parameter, try to extract the format string from the image if possible.
def _analyze_fmt_str_aarch64(image,base,sig):
with open(image,'r') as f:
for n in sig.nodes():
if not 'exit_func_name' in sig.node[n]:
continue
fmt_reg = fmt_func_map_aarch64.get(sig.node[n]['exit_func_name'],None)
if fmt_reg is None:
continue
formulas = sig.node[n]['formulas']
addr_ast = None
for k in formulas:
if fmt_reg in formulas[k]:
addr_ast = formulas[k][fmt_reg]
break
if addr_ast is None:
#Maybe the register is assigned a value in other nodes, we'll see..
print('!!! Cannot find the formulas for fmt arg reg %s in node %x' % (fmt_reg,n.addr))
continue
#OK, we get the addr ast for the fmt string.
#For now we only process the concrete addr.
addr = None
for a in addr_ast:
if a.op == 'BVV':
addr = a.args[0]
break
if addr is None:
print('No concrete addr found in: ' + str(addr_ast))
continue
#Finally... Extract the string from image.
offset = addr - base
f.seek(-1,2)
size = f.tell()
if offset < 0 or offset > size:
#print 'Addr %x out bound.' % addr
continue
f.seek(offset)
fmt_str = ''
while True:
c = f.read(1)
if c == '\0':
break
else:
fmt_str += c
if fmt_str != '':
sig.node[n]['fmt_str'] = fmt_str
#This intends to
#(1) reduce the redundant formulas stored in signature.
#(2) extract 'if' terms from state_merge related ITEs.
def simplify_signature(sig):
#Deduplicate based on str rep.
def _dedup(tlist):
seen = set()
def _f1(x):
x = x if type(x).__name__ in ('tuple','list') else [x]
s = str(_sig_get_str(x))
if s in seen:
return False
else:
seen.add(s)
return True
return list(filter(_f1,tlist))
for node in sig.nodes():
if 'padding' in sig.node[node]:
continue
for addr in sig.node[node]['formulas']:
inf = sig.node[node]['formulas'][addr]
if 'a-d-l' in inf:
r = []
for e in inf['a-d-l']:
r += excavate_if_tuple(e)
inf['a-d-l'] = _dedup(r)
elif 'a-g-k' in inf:
r = []
for e in inf['a-g-k']:
r += excavate_if_tuple(e)
inf['a-g-k'] = _dedup(r)
else:
for k in inf:
if k in ('type'):
continue
if isinstance(inf[k],list):
r = []
for e in inf[k]:
t = excavate_if(e)
r += [x[1] for x in t]
inf[k] = _dedup(r)
def excavate_if_tuple(t):
terms = [excavate_if(e) for e in t]
res = []
def _is_consistent(cl):
seen = set()
for e in cl:
for i in e:
if str(claripy.Not(i)) in seen:
return False
else:
seen.add(str(i))
return True
for e in itertools.product(*terms):
if _is_consistent([x[0] for x in e]):
#e: ((),(),..)
res += [tuple([x[1] for x in e])]
return res
#Excavate the 'if' conditions and ignore all 'state_merge' conditions.
def excavate_if(f):
if not isinstance(f,claripy.ast.Base):
return [([],f)]
fs = [([],f)]
prev = 0
while len(fs) > prev:
prev = len(fs)
new = []
for e in fs:
ee = e[1].ite_excavated
if ee.op == 'If':
if is_state_merge_condition(ee.args[0]):
new += [(e[0]+[ee.args[0]],ee.args[1]),(e[0]+[claripy.Not(ee.args[0])],ee.args[2])]
else:
#TODO: What can we do here? Maybe a deeper excavation..