Python: ReDoS conservative

config/identical-files.json

@@ -448,5 +448,17 @@
   "SensitiveDataHeuristics Python/JS": [
     "javascript/ql/src/semmle/javascript/security/internal/SensitiveDataHeuristics.qll",
     "python/ql/src/semmle/python/security/internal/SensitiveDataHeuristics.qll"
+  ],
+  "ReDoS Util Python/JS": [
+    "javascript/ql/src/semmle/javascript/security/performance/ReDoSUtil.qll",
+    "python/ql/src/semmle/python/regex/ReDoSUtil.qll"
+  ],
+  "ReDoS Exponential Python/JS": [
+    "javascript/ql/src/semmle/javascript/security/performance/ExponentialBackTracking.qll",
+    "python/ql/src/semmle/python/regex/ExponentialBackTracking.qll"
+  ],
+  "ReDoS Polynomial Python/JS": [
+    "javascript/ql/src/semmle/javascript/security/performance/SuperlinearBackTracking.qll",
+    "python/ql/src/semmle/python/regex/SuperlinearBackTracking.qll"
   ]
 }

javascript/ql/src/Performance/ReDoS.ql

@@ -14,328 +14,7 @@
 
 import javascript
 import semmle.javascript.security.performance.ReDoSUtil
-
-/*
- * This query implements the analysis described in the following two papers:
- *
- *   James Kirrage, Asiri Rathnayake, Hayo Thielecke: Static Analysis for
- *     Regular Expression Denial-of-Service Attacks. NSS 2013.
- *     (http://www.cs.bham.ac.uk/~hxt/research/reg-exp-sec.pdf)
- *   Asiri Rathnayake, Hayo Thielecke: Static Analysis for Regular Expression
- *     Exponential Runtime via Substructural Logics. 2014.
- *     (https://www.cs.bham.ac.uk/~hxt/research/redos_full.pdf)
- *
- * The basic idea is to search for overlapping cycles in the NFA, that is,
- * states `q` such that there are two distinct paths from `q` to itself
- * that consume the same word `w`.
- *
- * For any such state `q`, an attack string can be constructed as follows:
- * concatenate a prefix `v` that takes the NFA to `q` with `n` copies of
- * the word `w` that leads back to `q` along two different paths, followed
- * by a suffix `x` that is _not_ accepted in state `q`. A backtracking
- * implementation will need to explore at least 2^n different ways of going
- * from `q` back to itself while trying to match the `n` copies of `w`
- * before finally giving up.
- *
- * Now in order to identify overlapping cycles, all we have to do is find
- * pumpable forks, that is, states `q` that can transition to two different
- * states `r1` and `r2` on the same input symbol `c`, such that there are
- * paths from both `r1` and `r2` to `q` that consume the same word. The latter
- * condition is equivalent to saying that `(q, q)` is reachable from `(r1, r2)`
- * in the product NFA.
- *
- * This is what the query does. It makes a simple attempt to construct a
- * prefix `v` leading into `q`, but only to improve the alert message.
- * And the query tries to prove the existence of a suffix that ensures
- * rejection. This check might fail, which can cause false positives.
- *
- * Finally, sometimes it depends on the translation whether the NFA generated
- * for a regular expression has a pumpable fork or not. We implement one
- * particular translation, which may result in false positives or negatives
- * relative to some particular JavaScript engine.
- *
- * More precisely, the query constructs an NFA from a regular expression `r`
- * as follows:
- *
- *   * Every sub-term `t` gives rise to an NFA state `Match(t,i)`, representing
- *     the state of the automaton before attempting to match the `i`th character in `t`.
- *   * There is one accepting state `Accept(r)`.
- *   * There is a special `AcceptAnySuffix(r)` state, which accepts any suffix string
- *     by using an epsilon transition to `Accept(r)` and an any transition to itself.
- *   * Transitions between states may be labelled with epsilon, or an abstract
- *     input symbol.
- *   * Each abstract input symbol represents a set of concrete input characters:
- *     either a single character, a set of characters represented by a
- *     character class, or the set of all characters.
- *   * The product automaton is constructed lazily, starting with pair states
- *     `(q, q)` where `q` is a fork, and proceding along an over-approximate
- *     step relation.
- *   * The over-approximate step relation allows transitions along pairs of
- *     abstract input symbols where the symbols have overlap in the characters they accept.
- *   * Once a trace of pairs of abstract input symbols that leads from a fork
- *     back to itself has been identified, we attempt to construct a concrete
- *     string corresponding to it, which may fail.
- *   * Lastly we ensure that any state reached by repeating `n` copies of `w` has
- *     a suffix `x` (possible empty) that is most likely __not__ accepted.
- */
-
-/**
- * Holds if state `s` might be inside a backtracking repetition.
- */
-pragma[noinline]
-predicate stateInsideBacktracking(State s) {
-  s.getRepr().getParent*() instanceof MaybeBacktrackingRepetition
-}
-
-/**
- * A infinitely repeating quantifier that might backtrack.
- */
-class MaybeBacktrackingRepetition extends InfiniteRepetitionQuantifier {
-  MaybeBacktrackingRepetition() {
-    exists(RegExpTerm child |
-      child instanceof RegExpAlt or
-      child instanceof RegExpQuantifier
-    |
-      child.getParent+() = this
-    )
-  }
-}
-
-/**
- * A state in the product automaton.
- *
- * We lazily only construct those states that we are actually
- * going to need: `(q, q)` for every fork state `q`, and any
- * pair of states that can be reached from a pair that we have
- * already constructed. To cut down on the number of states,
- * we only represent states `(q1, q2)` where `q1` is lexicographically
- * no bigger than `q2`.
- *
- * States are only constructed if both states in the pair are
- * inside a repetition that might backtrack.
- */
-newtype TStatePair =
-  MkStatePair(State q1, State q2) {
-    isFork(q1, _, _, _, _) and q2 = q1
-    or
-    (step(_, _, _, q1, q2) or step(_, _, _, q2, q1)) and
-    rankState(q1) <= rankState(q2)
-  }
-
-/**
- * Gets a unique number for a `state`.
- * Is used to create an ordering of states, where states with the same `toString()` will be ordered differently.
- */
-int rankState(State state) {
-  state =
-    rank[result](State s, Location l |
-      l = s.getRepr().getLocation()
-    |
-      s order by l.getStartLine(), l.getStartColumn(), s.toString()
-    )
-}
-
-class StatePair extends TStatePair {
-  State q1;
-  State q2;
-
-  StatePair() { this = MkStatePair(q1, q2) }
-
-  string toString() { result = "(" + q1 + ", " + q2 + ")" }
-
-  State getLeft() { result = q1 }
-
-  State getRight() { result = q2 }
-}
-
-predicate isStatePair(StatePair p) { any() }
-
-predicate delta2(StatePair q, StatePair r) { step(q, _, _, r) }
-
-/**
- * Gets the minimum length of a path from `q` to `r` in the
- * product automaton.
- */
-int statePairDist(StatePair q, StatePair r) =
-  shortestDistances(isStatePair/1, delta2/2)(q, r, result)
-
-/**
- * Holds if there are transitions from `q` to `r1` and from `q` to `r2`
- * labelled with `s1` and `s2`, respectively, where `s1` and `s2` do not
- * trivially have an empty intersection.
- *
- * This predicate only holds for states associated with regular expressions
- * that have at least one repetition quantifier in them (otherwise the
- * expression cannot be vulnerable to ReDoS attacks anyway).
- */
-pragma[noopt]
-predicate isFork(State q, InputSymbol s1, InputSymbol s2, State r1, State r2) {
-  stateInsideBacktracking(q) and
-  exists(State q1, State q2 |
-    q1 = epsilonSucc*(q) and
-    delta(q1, s1, r1) and
-    q2 = epsilonSucc*(q) and
-    delta(q2, s2, r2) and
-    // Use pragma[noopt] to prevent intersect(s1,s2) from being the starting point of the join.
-    // From (s1,s2) it would find a huge number of intermediate state pairs (q1,q2) originating from different literals,
-    // and discover at the end that no `q` can reach both `q1` and `q2` by epsilon transitions.
-    exists(intersect(s1, s2))
-  |
-    s1 != s2
-    or
-    r1 != r2
-    or
-    r1 = r2 and q1 != q2
-    or
-    // If q can reach itself by epsilon transitions, then there are two distinct paths to the q1/q2 state:
-    // one that uses the loop and one that doesn't. The engine will separately attempt to match with each path,
-    // despite ending in the same state. The "fork" thus arises from the choice of whether to use the loop or not.
-    // To avoid every state in the loop becoming a fork state,
-    // we arbitrarily pick the InfiniteRepetitionQuantifier state as the canonical fork state for the loop
-    // (every epsilon-loop must contain such a state).
-    //
-    // We additionally require that the there exists another InfiniteRepetitionQuantifier `mid` on the path from `q` to itself.
-    // This is done to avoid flagging regular expressions such as `/(a?)*b/` - that only has polynomial runtime, and is detected by `js/polynomial-redos`.
-    // The below code is therefore a heuritic, that only flags regular expressions such as `/(a*)*b/`,
-    // and does not flag regular expressions such as `/(a?b?)c/`, but the latter pattern is not used frequently.
-    r1 = r2 and
-    q1 = q2 and
-    epsilonSucc+(q) = q and
-    exists(RegExpTerm term | term = q.getRepr() | term instanceof InfiniteRepetitionQuantifier) and
-    // One of the mid states is an infinite quantifier itself	
-    exists(State mid, RegExpTerm term |
-      mid = epsilonSucc+(q) and
-      term = mid.getRepr() and
-      term instanceof InfiniteRepetitionQuantifier and
-      q = epsilonSucc+(mid) and
-      not mid = q
-    )
-  ) and
-  stateInsideBacktracking(r1) and
-  stateInsideBacktracking(r2)
-}
-
-/**
- * Gets the state pair `(q1, q2)` or `(q2, q1)`; note that only
- * one or the other is defined.
- */
-StatePair mkStatePair(State q1, State q2) {
-  result = MkStatePair(q1, q2) or result = MkStatePair(q2, q1)
-}
-
-/**
- * Holds if there are transitions from the components of `q` to the corresponding
- * components of `r` labelled with `s1` and `s2`, respectively.
- */
-predicate step(StatePair q, InputSymbol s1, InputSymbol s2, StatePair r) {
-  exists(State r1, State r2 | step(q, s1, s2, r1, r2) and r = mkStatePair(r1, r2))
-}
-
-/**
- * Holds if there are transitions from the components of `q` to `r1` and `r2`
- * labelled with `s1` and `s2`, respectively.
- *
- * We only consider transitions where the resulting states `(r1, r2)` are both
- * inside a repetition that might backtrack.
- */
-pragma[noopt]
-predicate step(StatePair q, InputSymbol s1, InputSymbol s2, State r1, State r2) {
-  exists(State q1, State q2 | q.getLeft() = q1 and q.getRight() = q2 |
-    deltaClosed(q1, s1, r1) and
-    deltaClosed(q2, s2, r2) and
-    // use noopt to force the join on `intersect` to happen last.
-    exists(intersect(s1, s2))
-  ) and
-  stateInsideBacktracking(r1) and
-  stateInsideBacktracking(r2)
-}
-
-private newtype TTrace =
-  Nil() or
-  Step(InputSymbol s1, InputSymbol s2, TTrace t) {
-    exists(StatePair p |
-      isReachableFromFork(_, p, t, _) and
-      step(p, s1, s2, _)
-    )
-    or
-    t = Nil() and isFork(_, s1, s2, _, _)
-  }
-
-/**
- * A list of pairs of input symbols that describe a path in the product automaton
- * starting from some fork state.
- */
-class Trace extends TTrace {
-  string toString() {
-    this = Nil() and result = "Nil()"
-    or
-    exists(InputSymbol s1, InputSymbol s2, Trace t | this = Step(s1, s2, t) |
-      result = "Step(" + s1 + ", " + s2 + ", " + t + ")"
-    )
-  }
-}
-
-/**
- * Gets a string corresponding to the trace `t`.
- */
-string concretise(Trace t) {
-  t = Nil() and result = ""
-  or
-  exists(InputSymbol s1, InputSymbol s2, Trace rest | t = Step(s1, s2, rest) |
-    result = concretise(rest) + intersect(s1, s2)
-  )
-}
-
-/**
- * Holds if `r` is reachable from `(fork, fork)` under input `w`, and there is
- * a path from `r` back to `(fork, fork)` with `rem` steps.
- */
-predicate isReachableFromFork(State fork, StatePair r, Trace w, int rem) {
-  // base case
-  exists(InputSymbol s1, InputSymbol s2, State q1, State q2 |
-    isFork(fork, s1, s2, q1, q2) and
-    r = MkStatePair(q1, q2) and
-    w = Step(s1, s2, Nil()) and
-    rem = statePairDist(r, MkStatePair(fork, fork))
-  )
-  or
-  // recursive case
-  exists(StatePair p, Trace v, InputSymbol s1, InputSymbol s2 |
-    isReachableFromFork(fork, p, v, rem + 1) and
-    step(p, s1, s2, r) and
-    w = Step(s1, s2, v) and
-    rem >= statePairDist(r, MkStatePair(fork, fork))
-  )
-}
-
-/**
- * Gets a state in the product automaton from which `(fork, fork)` is
- * reachable in zero or more epsilon transitions.
- */
-StatePair getAForkPair(State fork) {
-  isFork(fork, _, _, _, _) and
-  result = MkStatePair(epsilonPred*(fork), epsilonPred*(fork))
-}
-
-/**
- * Holds if `fork` is a pumpable fork with word `w`.
- */
-predicate isPumpable(State fork, string w) {
-  exists(StatePair q, Trace t |
-    isReachableFromFork(fork, q, t, _) and
-    q = getAForkPair(fork) and
-    w = concretise(t)
-  )
-}
-
-/**
- * An instantiation of `ReDoSConfiguration` for exponential backtracking.
- */
-class ExponentialReDoSConfiguration extends ReDoSConfiguration {
-  ExponentialReDoSConfiguration() { this = "ExponentialReDoSConfiguration" }
-
-  override predicate isReDoSCandidate(State state, string pump) { isPumpable(state, pump) }
-}
+import semmle.javascript.security.performance.ExponentialBackTracking
 
 from RegExpTerm t, string pump, State s, string prefixMsg
 where hasReDoSResult(t, pump, s, prefixMsg)